AI Engineering Jobs

We're hiring a passionate, driven, AI-obsessed Community Manager at AI Engineer! 400% growth in two years. 10,000+ attendees projected by 2030. The biggest vendor-neutral event in AI.

You'll be building the whole thing — global meetup programs, ambassador network, education hub, associate program, 360 community support — as well as strengthening our large-scale events with community-first activations. And you'll be doing it for an audience of the most talented AI engineers on the planet.

You'll thrive here if you: Use AI tools every day. Know the difference between building an audience and building a community. Can run 10 projects at once without dropping anything. Get genuinely excited about making developers feel like they belong somewhere.

Requirements: 5+ years in community, events, and developer programs. Remote-first (USA). Real ownership, real reward, and real impact.

Ampersand is hiring our first Founding Marketer — someone who’s equal parts technical tinkerer, empathetic storyteller, and relentless shipper. You’ll work directly with our founding team to help 1000x our usage chart and bring Ampersand to every AI developer building customer-facing products.

We’re building the integration platform for an agentic world: real-time, enterprise-grade sync infrastructure that lets AI developers connect to customer systems like Salesforce, DealCloud, or Snowflake — without becoming an integration company.

We're hiring a Forward Deployed Engineer to work directly inside customer environments, implementing and extending Ampersand in a way that makes each deployment succeed and teaches us something we can build on.

This role is part engineer, part technical advisor, part trusted partner. You'll work closely with strategic customers from kickoff through delivery, write production code when the work calls for it, and bring what you learn back to the core product and engineering team.

We're hiring a Sales Engineer to be the technical core of a GTM team that sells a complex, infrastructure-level product to buyers who know exactly what they're evaluating.

The buyers are engineers, CTOs, and product leaders. Demos are technical. Evaluations go deep. You'll partner closely with Account Executives to move deals forward, owning the technical side of the sales process from discovery through proof-of-concept and close.

We're hiring a Founding Design Engineer to shape the user experience of a platform used by some of the most technically sophisticated teams in software and AI.

This is a foundational role. You'll work closely with the founders, engineers, and customers to design experiences for complex, developer-facing workflows — and help establish the design standards the product will be built on from here.

We're hiring a Product Engineer to work on the core platform that powers Ampersand's integration infrastructure.

You'll work closely with the founders, engineers, and customers to build the systems that power complex, developer-facing workflows.

We're hiring a Customer Engineer to serve as the technical backbone of our customer relationships, from first implementation through long-term success.

You'll work directly with technical customers to design and deploy solutions, solve complex integration challenges, and make sure they get real value from the platform.

We're looking for a Founding Engineering Manager to join a fast-growing AI infrastructure company at a pivotal moment. You'll work directly with the founders and a small, high-retention engineering team.

This is a hands-on role. You'll be close to the technical work, close to the people doing it, and close to the decisions that shape how the team grows.

We’re looking for a Head of Brand to define and amplify Apify's voice in the global market and make Apify a distinctive brand. We need someone who can craft a compelling brand narrative that resonates with developers, enterprise leaders, and the broader AI ecosystem. You will be the architect of how the world perceives Apify. You will drive our presence at global events, shape our social media voice, and launch campaigns that make Apify synonymous with the future of web data.

The Opportunity As an AI Solutions Manager, you’ll partner with some of the most innovative AI/ML teams in the world. You’ll play a pivotal role in driving adoption, shaping product use cases, and ensuring our customers succeed in leveraging AI to achieve real-world impact. This role offers a unique chance to grow alongside a leading AI company and gain deep insights into cutting-edge AI/ML applications. While we are a remote-first company, the nature of this role requires candidates to be based in the San Francisco Bay area/PST time zone.

The Team Our engineering team builds systems that interact with some of the most complex software ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more.

As an AI Solutions Manager, your work will directly contribute to our customers’ success in deploying impactful AI solutions, ensuring their models achieve measurable business outcomes. We are looking for a fast-paced, client-obsessed candidate with an entrepreneurial mindset to nurture, and grow our customers. You’ll be working with Arize customers to help them improve the AI they use across their organizations. You will be in charge of driving customer adoption and managing customers through their renewal cycles. You’ll accomplish this by running an effective account plan, identifying expansion opportunities with new teams, and building solutions to help achieve their goals. You’ll be involved in exciting and complex customer use cases and leverage your business acumen to navigate the intricacies.

About Arize AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That’s where we come in. Arize AI is the leading AI & Agent Engineering observability and evaluation platform, empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace—so teams can ship faster with confidence.

We’re a Series C company backed by top-tier investors, with over $135M in funding and a rapidly growing customer base of 150+ leading enterprises and Fortune 500 companies. Customers like Booking.com, Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works.

The Opportunity: We're looking for a driven Enterprise Expansion Account Executive to own and grow revenue within Arize's existing customer base. You'll work with AI engineers, Data Scientists, and platform teams who are already using our Enterprise platform - helping them unlock more value, expand into new teams, and deepen their investment as their AI initiatives scale. This is a high-impact, high-ownership role at the intersection of a fast-moving product and a customer base growing rapidly alongside the AI industry.

About Arize AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That’s where we come in. Arize AI is the leading AI & Agent Engineering observability and evaluation platform, empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace—so teams can ship faster with confidence.

We’re a Series C company backed by top-tier investors, with over $135M in funding and a rapidly growing customer base of 150+ leading enterprises and Fortune 500 companies. Customers like Booking.com, Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works.

The Opportunity Our engineering team builds systems that interact with some of the most complex software ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more.

As an AI Solutions Manager, you’ll partner with some of the most innovative AI/ML teams in the world. You’ll play a pivotal role in driving adoption, shaping product use cases, and ensuring our customers succeed in leveraging AI to achieve real-world impact. This role is a blend of solutions consulting, customer engagement, and AI product feedback. You’ll work directly with the ML and AI engineering teams at some of the most sophisticated companies in the world and help them observe, evaluate, and improve the AI they run in production.

You’ll own the customer lifecycle end to end: identifying the business problem, defining what success looks like with their stakeholders, shaping how Arize fits their architecture, and driving adoption through renewal and expansion. You’ll also feed what you learn back into the product, so solutions you build for one customer become repeatable for the next.

We're looking for a driven Enterprise Expansion Account Executive to own and grow revenue within Arize's existing customer base. You'll work with AI engineers, Data Scientists, and platform teams who are already using our Enterprise platform - helping them unlock more value, expand into new teams, and deepen their investment as their AI initiatives scale. This is a high-impact, high-ownership role at the intersection of a fast-moving product and a customer base growing rapidly alongside the AI industry.

Own the full expansion and renewal sales cycle across your book of business, executing a complex, value-based process that spans multiple stakeholders, teams, and use cases within each account.

Proactively identify and develop new growth opportunities by analyzing customer usage, mapping whitespace, and targeting high-value needs across business lines and technical teams.

Arize AI is the leading AI observability and evaluation platform, empowering AI engineers to build and deploy high-performing, reliable models. As the AI landscape shifts from traditional ML to generative AI and agentic systems, Arize ensures teams have the tools to monitor, troubleshoot, and improve AI in production.

Our Fullstack Engineering team builds both the highly scalable distributed services that power Arize's ML observability platform and the intuitive frontend applications that bring these capabilities to life. The team primarily works in TypeScript and Python to create seamless data visualization and monitoring experiences, with some services written in Go. We focus on delivering robust features that help clients interpret, visualize, and monitor their AI and ML models across the entire stack.

You will be a part of the core team that drives product innovation at Arize. You will be challenged with understanding how some of the most impactful engineering teams are developing AI and LLM-powered applications, and how to build the right tools to enable them to do their best work. Our product solutions range from clean APIs that magically instrument applications, interactive playgrounds for prompt engineering and agent development, or scaling up real-time evaluation infrastructure to handle millions of annotations per second

Our engineering team builds systems that interact with some of the most complex software ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more.

We are looking for a fast-paced, client-obsessed Account Executive with an entrepreneurial mindset to find, win and grow new customers. You’ll be searching for business while being an engaged member of the AI/ML community, identifying prospects who will benefit most from our solution. You’ll accomplish this by running an effective ground-game, talking to AI/ML leaders, identifying opportunities to help and building solutions to help achieve their goals. You’ll be involved in exciting and complex sales cycles and leverage your business acumen to navigate the intricacies. While we are a remote-first company, we are prioritizing candidates currently based in the New York City metro area/EST time zone.

Our Backend Engineering team builds all of the highly scalable distributed services that power Arize’s ML observability platform. While Go is our primary language for these distributed systems, the team also maintains services and tools written in Python, Java, and TypeScript. The expectation and scope of every individual on this team is high, whether it’s finding the most efficient way to compute model evaluation metrics across billions of data points, designing the next generation of our OLAP database architecture, or researching and implementing the latest dimensionality reduction techniques – you will never lack a technical challenge.

You will be a part of the core team that drives product innovation at Arize. You will be challenged with understanding how some of the most impactful engineering teams are developing AI and LLM-powered applications, and how to build the right tools to enable them to do their best work. Our product solutions range from clean APIs that magically instrument applications, interactive playgrounds for prompt engineering and agent development, or scaling up real-time evaluation infrastructure to handle millions of annotations per second.

Atlassian is building AI for how teams work together. Sign up to get on the Talent team's radar and be the first to know about roles that match your background.

Where carbon meets silicon. At AXQ, AI isn't a recent addition. It's how we've worked from the start. Our founders have applied machine learning to financial markets for the past decade, and ML now sits at the center of everything we do. That ranges from classical statistical methods run at scale to deep learning, transformers, generative AI and agentic research.

As a Quantitative Researcher, you'll apply these methods to finding alpha in global markets: turning noisy data into robust models with scientific rigor. We're deliberately lean, so you get big-firm infrastructure with small-firm ownership. New ideas often go live in days to weeks.

As an Infrastructure Software Engineer at Baseten, you'll build and maintain components of our ML inference platform that powers production AI applications. You'll contribute to the core infrastructure, enabling developers to deploy, scale, and monitor ML models with high performance.

Where We Are Engineers spend their days switching between dashboards, terminals, and observability tools. They diagnose issues, chase alerts, and do the repetitive work that keeps systems running. Most of it isn't hard. But it's constant. It crowds out the work that actually makes systems better.

Cleric is an AI SRE teammate. We autonomously diagnose production issues across complex distributed systems. Not just the big outages. The small stuff too. No fix is too small. Engineers can focus on building. Systems get more resilient because problems actually get addressed.

Think of it this way: coding agents are becoming the future of the IDE. Cleric is the equivalent for production operations. We're the future replacement for the dashboards and terminals where engineers who monitor production live today.

We are seeking a Technical Account Manager (TAM) to serve as the primary technical and strategic partner for our customers post-sale. This is a hybrid role, blending the technical depth of a TAM with the relationship ownership of a Customer Success Manager: you will onboard and enable new customers, provide hands-on AI/ML expertise (including on agentic AI systems), and act as a trusted advisor and extension of the customer's own team throughout their lifecycle with Comet. In addition to driving adoption and resolving technical challenges, you will identify and support expansion opportunities and help ensure customers renew while working with the Sales/ Account team.

What you'll do?

-own the full sales cycle across digital-native accounts: prospecting, qualification, discovery, technical validation, pricing, negotiation, close, and expansion

-run consultative sales conversations with technical buyers and translate agent/tooling problems into a clear Composio value story

What you'll do?

-own paid acquisition end to end across Meta, Google, YouTube, TikTok, and whatever channel starts working next

-build influencer, newsletter, podcast, and partnership channels for a technical audience

What you'll do?

-ship growth experiments across the stack - landing pages, onboarding flows, backend services, data pipelines, dashboards, and internal tools

-scope ruthlessly to get signal fast, then either kill the idea or build it properly

WHAT YOU'LL DO?

own the on-prem lifecycle: helm charts, upgrades, the weekly release train, rollback paths.

drive chart convergence: diverged customer forks back onto one supported chart, with guardrails.

What you'll do?

-tell us the job you would be exceptional at and why Composio should create space for it

-show us the work - products shipped, companies started, research, writing, open source, workflows, or anything else with real signal

What you'll do?

-define how the world talks about Composio - positioning, messaging, narrative, and proof across every surface

-own product launches end to end: angle, sequence, channels, assets, internal alignment, and post-launch learning

What you'll do?

-own the customer support queue end to end - triage, reproduce, fix, ship, close

-write code daily in Typescript and Python: small fixes, integration tweaks, SDK patches, and whatever the ticket needs

WHAT YOU'LL DO?

own enterprise accounts end to end: discovery, spec, implementation, QA, release.

ship production code in our toolkit monorepo and customer SDKs: custom and composite tools, schema and scope changes, per-customer patches.

What you'll do?

-manage a book of Composio's largest enterprise and growth accounts as their primary point of contact and internal advocate

-lead structured onboarding so customers reach value quickly with clean technical integration and clear success metrics

What you'll do?

-evolve our platform primitives and APIs — auth, automatic refreshes, triggers, tool search, tool planning, orchestrating and managing sandboxes

-manage multiple runtimes for code execution across lambdas and firecracker

What you'll do?

-own enterprise product end to end - pre-sales technical validation, POC support, weekly customer syncs, launch readiness, and post-launch iteration

-turn ambiguous enterprise requests into product decisions, design docs, tradeoffs, and timelines engineering can defend

What you'll do?

-elevate the experience of teams building on us, by improving our core APIs and SDK

-deliver elegant interfaces both on the frontend and the sdk

What you'll do?

-partner with members of the leadership team to manage calendars, coordinate scheduling, and keep day-to-day operations running smoothly so leaders can focus on high-leverage work.

-act as a generalist operator across the business, jumping into new systems and workflows to identify gaps, bring structure to ambiguous projects, and ship operational improvements end-to-end

What you'll do?

-follow up with inbound and outbound prospects across phone, email, LinkedIn, communities, and events

-uncover fit, urgency, pain, and potential value quickly enough to create useful meetings for Account Executives

What you'll do?

-build internal tooling on the fly to run our internal operations more smoothly

-own banking, treasury and cash management, vendor negotiations

What you'll do?

-own technical relationships with top accounts across discovery, architecture, integration planning, launch, and tuning

-build proofs of concept end to end in Typescript, Python, our SDK, and the customer stack

What you'll do?

-own the full sales cycle across enterprise accounts: prospecting, qualification, discovery, technical validation, pricing, negotiation, close, and expansion

-run consultative conversations with engineering, product, AI, security, and procurement stakeholders

What you'll do?

-build large evals with real tool calling data, measuring where models suck in long horizon tool execution

-work on search problems for finding semantically similar tools and cached tool execution paths and plans.

What you'll do?

-elevate the experience of teams building on us, by improving our core APIs and SDK

-deliver elegant interfaces both on the frontend and the sdk

What you'll do?

-own sourcing across every open role - Github, X, hackathon leaderboards, paper authors, open source communities, and the places our customers live

-run technical screens yourself: read code, ask useful follow-ups, and separate signal from noise

About the Role We're looking for an experienced Infrastructure Engineer to join as a member of our core Datology AI team. As one of our early senior hires, you will partner closely with our founders on the direction of our product and drive business-critical technical decisions. You will lead the development of our data infrastructure capabilities, including multi-cloud support and support for various deployment models, as well as training and inference infrastructure. You will have a broad impact on the technology, product, and our company's culture.

What You'll Work On Design and build the development and production platforms that power our products, enabling reliability and security at scale Architect, build, and deploy our core infrastructure while supporting multiple cloud providers and various deployment models Accelerate company productivity by empowering your fellow engineers & teammates with excellent tooling and systems, providing a best-in-case experience Partner with researchers and engineers to bring new features and research capabilities to our customers

About You 4+ years of relevant experience Have meaningful experience in spearheading and constructing large-scale infrastructure Proficiency in bash, Kubernetes, Python, and/or Terraform or similar technologies Have experience working with AWS, other cloud platforms such as Azure or GCP and/or on-prem environments Have expertise in debugging problems across the stack, such as networking issues, performance problems, hardware issues or memory leaks Take pride in building and operating scalable, reliable, secure systems Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done

About the Role We’re looking for an experienced Cloud Infrastructure Engineer to join our core team at DatologyAI. In this role, you will lead the design, build, and operation of highly available, secure, and scalable cloud infrastructure that powers our training, inference, and data curation pipelines. You’ll work closely with engineering, research, and product teams to define how we deploy and manage compute resources across AWS and other cloud providers. This role is a key early hire and offers an opportunity to have a deep technical and cultural impact.

What You'll Work On Architect and maintain our multi-cloud infrastructure (primarily AWS, potentially Azure/GCP), with a focus on reliability, security, and scalability Define and implement infrastructure-as-code best practices using Terraform, CloudFormation, Pulumi (and similar technologies) Design and manage Kubernetes-based systems for model training, inference, and data processing workloads Optimize our CI/CD pipelines and streamline deployment of services across environments Build monitoring, alerting, and logging systems to ensure high system availability and observability Collaborate with research and engineering teams to provide infrastructure support for training large-scale ML models Ensure our infrastructure supports various deployment models (cloud, on-prem, hybrid) for enterprise use cases Drive cost-efficiency strategies across compute and storage resources Respond to and resolve infrastructure-related incidents with a sense of ownership and urgency

About You 4+ years of relevant experience You’ve led or helped build robust infrastructure systems at a startup or fast-moving engineering organization Deep experience working with cloud providers (especially AWS), and ideally exposure to multi-cloud or hybrid-cloud setups Strong with Kubernetes, Terraform, and containerized architectures Confident with systems-level debugging—networking issues, memory leaks, resource bottlenecks, etc. Comfortable writing clean, maintainable scripts in Bash, Python, or Go You care deeply about building secure and scalable systems and take pride in reliable infrastructure You’re collaborative, humble, and ready to own high-impact projects end-to-end

About the Role As our first Product Manager, you will own the product strategy and roadmap for our enterprise data curation platform. This is a high-leverage, high-ownership role where you’ll build the function from the ground up. You'll work at the intersection of cutting-edge ML research and enterprise software, translating deep technical capabilities like automated data selection, deduplication, batching, multimodal curation at petabyte scale into a product that enterprise AI teams love to use.

You'll partner closely with the founders, our research, engineering teams to define what we build and why. This role will shape how Datology evolves from a technically differentiated platform into a category-defining AI tooling company.

What You'll Work On Own the product roadmap end-to-end: from discovery and prioritization through launch and iteration, with a focus on enterprise-grade AI tooling Partner with research and engineering to turn ambiguous, early-stage outputs into concrete, shippable product decisions. Define and drive the enterprise product experience -- including platform UX, API design, deployment flexibility (BYOC, on-prem), and integrations with existing ML workflows Develop deep customer intuition by engaging directly with enterprise ML teams, data scientists, and infrastructure engineers -- turning their pain points into a clear product strategy Build the foundational PM infrastructure: discovery frameworks, roadmap tooling, release processes, and cross-functional rituals that scale as the team grows Work with Sales and Customer Success to ensure the product enables a repeatable, defensible go-to-market motion Track the competitive landscape across AI tooling, MLOps, and data infrastructure to inform positioning and prioritization Serve as the connective tissue between research output and commercial product -- helping the team decide what to build, sequence how, and measure whether it's working

About the Role We're looking for an experienced Data Platform Engineer to join as a member of our core Engineering team. As one of our senior hires, you will partner closely with our founders on the direction of our product and drive business-critical technical decisions. You will lead the development of our core product and data platform. These are key components of our stack that allow us to process customer data and apply state of the art research for identifying the most informative data points in large-scale datasets. You will have a broad impact over the technology, product, and our company's culture. We provide visa sponsorship for candidates selected for this role.

What You'll Work On Design, build and maintain highly scalable data processing solutions, while ensuring scalability, reliability, and security Architect, build, and deploy the back-end systems and services that power our data curation platform Partner with researchers and engineers to bring new features and research capabilities to our customers Ensure that our systems are reliable, secure, and worthy of our customers' trust

About You 4+ years of experience in data engineering, including owning production systems end-to-end -- scalable processing (Spark, Flink), storage (HDFS, S3), lakes/warehouses (Snowflake, Hive), SQL, and workflow orchestration (Airflow, Dagster). Proficiency in Python, Scala, or Java. Experience as a technical lead of a Data Engineering, Platform, or Infrastructure team. Experience building ML/DL systems or data infrastructure that feeds large-scale model training. High bar for design, correctness, and testing. You build systems that are scalable, reliable, and secure. Low ego, high ownership. You help your teammates, pick up whatever's needed, and see problems through to completion.

About Etched

Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history.

Job Summary

About Etched

Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history.

Job Summary

Flox is hiring a Solutions Engineer to support the full-stack of sales from discovery to close. You're the person who can sit across from a staff engineer at a Fortune 5 company, open a terminal, and earn trust in the first ten minutes.

Flox has strong inbound, so you'll run multiple evaluations in parallel and need to hold quality across all of them. Execution without judgment produces noise. Narrative without a working demo produces slideware. We want both.

This is Flox’s first dedicated security hire. You’ll work directly with engineering leadership to stand up security practices that are pragmatic, developer-friendly, and right-sized for a company at our stage. The role is heavily weighted toward doing—you’ll be the one deploying tools, configuring controls, hardening infrastructure, and closing gaps, not just advising others to do so.

That said, you’ll have real input into how we think about controls, priorities, and our security roadmap as we grow. And because our product sits at the heart of the software supply chain—managing dependencies, environments, and build artifacts for some of the world’s largest engineering teams—security isn’t peripheral here. It’s core to the value we deliver.

If you want to build something from scratch, own it end-to-end, and have your work matter immediately, this is that job. If you want a large team, an existing program to slot into, or mostly governance work, it probably isn’t.

About the Role We are looking for a Senior Full Stack Engineer with a strong frontend orientation to help build next-generation collaborative AI-powered product experiences. This role is ideal for someone who thrives in fast-paced startup environments and enjoys building polished, user-centric applications that blend creativity, AI, and real-time collaboration.

You will work closely with product, design, and engineering teams to create highly interactive web and mobile experiences where humans and AI agents collaborate seamlessly.

We’re a very small, fast-moving engineering team building a live AI product used in the real world. Today, that team is just two engineers — and we’re looking for a senior full-stack engineer who wants real ownership, not pre-written tickets.

This role is closer to a founding engineer than a traditional IC position. You’ll work directly with the CTO to turn loosely defined ideas into shipped features. That means designing data models, writing backend logic, crafting frontend experiences, and wiring AI systems together — often in the same week.

If you enjoy ambiguity, value momentum over perfection, and like seeing your work reach users quickly, you’ll fit right in.

About the Company We are a fast-growing financial technology company building modern infrastructure that bridges traditional financial systems with emerging digital asset technologies. Our platform enables secure, compliant, and scalable access to financial products through innovative technology solutions.

Operating in a highly regulated environment requires a strong focus on security, reliability, automation, and operational excellence. We are seeking a skilled DevOps & Security Engineer to help scale our cloud infrastructure, strengthen our security posture, and improve system observability across mission-critical services.

Position Overview As a DevOps & Security Engineer, you will play a key role in designing, automating, and securing cloud infrastructure while supporting development teams in delivering reliable software at scale. This position sits at the intersection of engineering, operations, and security, with a strong emphasis on automation, infrastructure as code, monitoring, and compliance.

Our team works at the intersection of Engineering, Product, and Community. You will work in the emerging benchmark ecosystem to onboard external benchmarks to Kaggle. Through collaborative engineering, joint benchmarking, and feedback loops, we run systematic evaluations to accelerate model capability understanding.

The Forward Deployed Engineer is the technical bridge between DeepMind’s most strategic partners and our model research teams. This role is embedded in the partner’s engineering journey, building joint evals, unblocking complex integrations, and synthesizing deep technical signals to drive model improvements.

Greptile is an AI code reviewer that catches bugs and anti-patterns in pull requests with complete context of the codebase. Hundreds of top software companies use Greptile to merge PRs faster and prevent bugs.

Solve some of our hardest and most interesting problems, including LLM memory, multi-language codebase indexing, semantic search for large codebases, and much more.

About Keycard At Keycard, we’re building identity & access infrastructure for the agent-native era—where software isn’t static, but a dynamic, constantly changing system of AI agents working on behalf of people and businesses to complete dynamic tasks at runtime.

Our mission is to unlock the agent economy by empowering developers and enterprises with the secure, scalable foundations they need to build, deploy, adopt, and trust agentic applications. To do this, we’re building the real-time, in-band, contextual guardrails required to transition from human-driven to truly autonomous and agentic workflows that give users, builders, and security teams the confidence and control they need to bring agents out of the lab and into production.

At our core, we’re laser-focused on delivering a delightful, best-in-class developer experience that gives them the tools they need to create category-defining applications and experiences while giving platform and security teams the security, scalability, visibility, control, and enablement they need to accelerate their organizations journey to becoming agent native.

About Keycard At Keycard, we’re building identity & access infrastructure for the agent-native era—where software isn’t static, but a dynamic, constantly changing system of AI agents working on behalf of people and businesses to complete dynamic tasks at runtime.

Our mission is to unlock the agent economy by empowering developers and enterprises with the secure, scalable foundations they need to build, deploy, adopt, and trust agentic applications. To do this, we’re building the real-time, in-band, contextual guardrails required to transition from human-driven to truly autonomous and agentic workflows that give users, builders, and security teams the confidence and control they need to bring agents out of the lab and into production.

At our core, we’re laser-focused on delivering a delightful, best-in-class developer experience that gives them the tools they need to create category-defining applications and experiences while giving platform and security teams the security, scalability, visibility, control, and enablement they need to accelerate their organizations journey to becoming agent native.

About Keycard At Keycard, we’re building identity & access infrastructure for the agent-native era—where software isn’t static, but a dynamic, constantly changing system of AI agents working on behalf of people and businesses to complete dynamic tasks at runtime.

Our mission is to unlock the agent economy by empowering developers and enterprises with the secure, scalable foundations they need to build, deploy, adopt, and trust agentic applications. To do this, we’re building the real-time, in-band, contextual guardrails required to transition from human-driven to truly autonomous and agentic workflows that give users, builders, and security teams the confidence and control they need to bring agents out of the lab and into production.

At our core, we’re laser-focused on delivering a delightful, best-in-class developer experience that gives them the tools they need to create category-defining applications and experiences while giving platform and security teams the security, scalability, visibility, control, and enablement they need to accelerate their organizations journey to becoming agent native.

Keycard is building identity and access infrastructure for agents. The platform gives developers and enterprises real-time guardrails and contextual controls so they can build agentic applications people can trust. The founding team has built companies before at Snyk, Auth0, HashiCorp, and Heroku.

As PM for Growth & Developer Experience, you'll own how developers discover, evaluate, and adopt Keycard. That covers everything from SDK quickstarts and CLI onboarding to console setup, docs, and template repos. Your main goal is to cut the time it takes a developer to complete their first credential exchange. You'll also push for clean API and CLI design, and turn work that field engineers do by hand into self-guided evaluation paths. You'll set the metrics and work with engineering and go-to-market teams to hit them.

You'll fit well if you've been a PM on developer products and cared about adoption metrics. You should be credible with engineers: able to judge a quickstart, follow an API design discussion, and query the data yourself. You should use AI tools every day and have informed opinions about the agent ecosystem. You set up instrumentation before drawing conclusions, you're comfortable in a new category without a playbook, and you write clearly. It's a plus if you've shipped code, or know OAuth, OIDC, token exchange, or agent protocols like MCP and A2A.

We are hiring several phenomenal Full Stack TypeScript Developers with experience writing high-quality TypeScript code and additional knowledge of cloud deployment like serverless architectures (Cloudflare/AWS/Azure). In this role, you will contribute to the development and enhancement of our platform, ensuring seamless integration and optimal performance.

Work on some of the hardest problems in applied AI alongside customers. This is not demos or research — you'll help teams build systems they rely on in production. Co-architect and co-build production AI agents with customer engineering teams, own the technical win in pre-sales, and advise customers on architecture and best practices.

Requires 3+ years in a relevant technical role, strong Python/JavaScript fundamentals, and experience designing agent-based or LLM-powered applications beyond simple API calls. This role requires 40% travel to customer sites.

As Meticulous's first Forward Deployed Engineer in San Francisco, you'll establish the US FDE presence and help define how the function operates from the ground up. Work directly with engineering leaders at the world's most AI-driven companies, understanding their unique architectures and crafting solutions for their specific needs.

Meticulous is building the last piece of the puzzle to help companies unlock AI code generation — the part that makes it actually safe to ship. Backed by investors behind Twilio, Twitch, Intercom, and PagerDuty, with customers including Notion, ElevenLabs, Dropbox, Discord, and more.

The Code|AI team is the Applied Research and Data for Github Copilot and VS Code, working on the future of AI for Developers! We are a diverse, entrepreneurial, and multi-disciplinary group of scientists, researchers, and engineers with a passion for using AI to improve the productivity of millions of developers around the world. We have released AI for code advancements in Github Copilot, VS Code, Visual Studio and Copilot extensions in other IDEs. Our team focuses on post-training code specific models like code completion, code embedding models and agentic research for Copilot Coding Agent, Copilot CLI and Copilot Code Review. We embrace the open source and continue to share our research and work with the developer and research community to advance AI in Developer tools.

We are seeking entrepreneurial and creative Applied Researchers 2/ Senior Applied Researchers - CoreAI to lead groundbreaking research projects, taking these from research into product. You will collaborate with scientists, engineers and designers across Microsoft Research, Microsoft product teams, and Github. You will have an opportunity to build and train state-of-the-art models, and opportunities to both apply and advance existing approaches of using LLMs for software engineering, from using RAG to evaluation. Most importantly, you will have an opportunity to work closely with several developer product teams to run experiments, evaluate, iterate, and improve your AI projects on a large scale.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Microsoft Research (MSR) is a multidisciplinary global organization working to create scientific knowledge and deliver innovation that leads to positive human impact at scale. To envision and build the future, we work with our scientific, engineering, academic and business partners to use Machine Learning and Artificial Intelligence (AI) to impact economics, health and society. The Microsoft Research Americas Engineering team supports several MSR labs (Redmond, New England, New York City, and Montreal) and seeks an innovative and experienced Senior Research Software Engineer on the Agentic Experiences team to drive and contribute to a variety of research projects in various stages of research and productization. You will help deliver quality engineering solutions engaging in AI-native development methods, automation, and agentic workflows to design, build, evaluate, and ship software across Microsoft Research. You will collaborate with other engineers, researchers, and product teams to create innovative vision and drive high quality execution for high-impact and high-scale reach across all of Microsoft’s portfolio, from core models, health, social and economics, coding and development, vision and graphics, systems and networks, and more. You will also be able to contribute to the shape our engineering culture, strategy, and execution, as well as modernize AI engineering practices all in support of accelerating our collective impact across Microsoft Research Americas, Microsoft and beyond.

At Microsoft, our mission—to empower every person and every organization on the planet to achieve more—guides how we partner with customers to deliver trusted, impactful solutions. With a growth mindset culture, we innovate responsibly and measure success by shared progress—people, teams, and customers. Join us to do meaningful work that changes the world and helps shape what’s next for everyone.

The Data and AI team in Microsoft’s Developer Division is working on the future of AI for Developers! We are a diverse, entrepreneurial and multi-disciplinary group of scientists, researchers and engineers with passion for using AI to improve the productivity of millions of developers around the world. We have released AI for code advancements in Github Copilot, VS Code, Visual Studio and other Microsoft Copilots.

We are seeking entrepreneurial and creative Principal Applied Researcher to lead groundbreaking research projects, taking these from research into product. You will collaborate with scientists, engineers and designers across Microsoft Research, Microsoft product teams and Github. You will have an opportunity to build and train state-of-the-art models, and opportunities to both apply and advance existing approaches of using LLMs for software engineering, from using RAG to evaluation. Most importantly, you will have an opportunity to work closely with several developer product teams to run experiments, evaluate, iterate and improve your AI projects on a large scale.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Mixedbread is an applied AI research and technology company building next-generation information retrieval systems for modern AI applications. We are looking for a Member of Technical Staff to work across research, engineering, product, and customer-facing technical initiatives.

You will help develop and improve AI retrieval and search systems; evaluate embedding models, multimodal search, LLM-based systems, and agentic retrieval; design rigorous evaluation frameworks; prototype new technical approaches; investigate quality, scalability, and reliability; and move promising research ideas into production.

This is a hands-on, high-ownership role for someone with strong machine-learning and software-engineering fundamentals who can turn ambiguous problems into experiments, prototypes, and production systems. Experience with information retrieval, embeddings, vector search, transformers, RAG, multimodal AI, or ML infrastructure is a plus.

Full-time · San Francisco · Reports to CEO / Founders. Competitive compensation and equity, visa sponsorship, and relocation support.

We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal's container runtime to push language and diffusion models towards higher throughput and lower latency, we'd love to hear from you!

We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform.

Lead the design and optimization of high-performance kernels for large-scale AI inference on GPUs and emerging custom accelerators. You'll own performance-critical paths, drive architectural decisions, and turn complex AI workloads into highly optimized implementations that run efficiently at scale.

Work at the intersection of hardware, compilers, and AI systems. Requires 5+ years in performance-critical systems, strong C/C++ and GPU kernel programming (CUDA, HIP). US or Canada, remote or in-office (Los Altos, CA).

Optiver is a seeking a Machine Learning Research Engineer to join our team, focusing on a pivotal AI initiative. This role would offer the opportunity to have significant impact across Machine Learning infrastructure, training, and inference challenges to advance our futures trading strategies.

Optiver is a seeking a Machine Learning Performance Engineer to join our team, focusing on a pivotal AI initiative. This role would offer the opportunity to have significant impact across Machine Learning infrastructure, training, and inference challenges to advance our futures trading strategies.

We are seeking a highly skilled and experienced AI Engineer to join our dynamic team. In this hands-on role, you’ll design, build, and deploy sophisticated agents that orchestrate data, workflows, and decisions across the firm. You’ll own the full lifecycle—from rapid prototyping through production rollout—while always tying technical choices back to clear business outcomes. If you can translate strategy into code, measure impact in dollars (or hours saved), and thrive in a fast-moving environment, we want to meet you.

The Optiver Research Platform (ORP) is a vertically integrated platform team that manages both high-performance compute infrastructure and the software platform layered on top. ORP enables Optiver’s global research teams to define and execute large-scale computational problems such as simulations and model training through streamlined orchestration of complex workflows. By owning the full stack, from datacenter hardware to distributed research tooling, ORP provides the fastest possible turnaround time for experiments and continually expands Optiver’s ability to generate insights from the markets we operate in.

We are hiring a senior/staff software engineer to help design and build core components of our next-generation knowledge retrieval system built for the AI era – search and retrieval infrastructure that powers high-quality, scalable, and enterprise-grade agentic systems. You’ll build the framework that allows our customers to connect knowledge–synthesized from structured and unstructured data–to modern LLM-powered applications, leveraging the world’s best-in-class vector DB supporting semantic search and hybrid retrieval. This role is ideal for someone who loves backend system architecture, distributed systems, and applied AI infrastructure. It is a high impact role with significant ownership across architecture, performance, and system reliability.

Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation

As a Senior Software Engineer, you will play a pivotal role in enhancing the security architecture of our platform. You’ll work closely with cross-functional teams to design, develop, and implement robust security solutions that adhere to the highest industry standards. Your contributions will directly impact the safety and integrity of organizations relying on Pomerium to secure their infrastructure.

PostHog is working on a self-driving product and is training its own Deep ML models for this, and to do this we have a new AI Research team.

We track more products across more dimensions than any other company on earth. Because of this, we have Petabytes of data across events, errors, session replays, revenue data and more. It's an exceptionally large amount of data relative to our company size and we want to use it for our users' benefit.

Just imagine how, with the vast amount of data we capture, we can automatically surface insights and suggest fixes.

As an AI Research Engineer, you will be a substantial part in making this happen. This team is brand new, so you will have real autonomy, be close to customers, and greatly influence what we actually ship.

Be our first Account Executive and drive commercial adoption of foundation models for structured data. This is a founding role: you'll shape how we sell, who we sell to, and what good looks like for every AE who joins after you. You'll work directly with the commercial founder and a team of ex-DeepMind, Palantir, Jane Street, Goldman Sachs, and Amazon researchers and operators.

The focus is outbound. You'll spend most of your time on outreach and discovery with technical buyers (data scientists, ML engineers, technical leaders), then run demos, build proposals, navigate buying committees, and own deals from qualification through signed contract. You'll also help write the playbook (qualification criteria, outbound sequences, demo structure, objection handling) that the next hires are built on, and bring field intelligence back to the team.

You bring 3+ years in a full-cycle AE role at a data infrastructure, ML tooling, developer tools, or deep tech company, a track record closing enterprise and mid-market deals with technical buyers, and proven outbound pipeline generation from scratch. You're technically literate enough to hold a credible conversation with an ML team, and you'd rather build the engine than inherit someone else's playbook.

Take tabular foundation models into the environments of our most strategic customers and own the work through to production. You'll integrate our models into customer platforms and pipelines, do the hands-on data science on real, messy data to prove value against their current baseline, and carry each use case from first conversation to a reliable, documented solution.

This is a senior role with high autonomy. You'll make hard technical calls under ambiguity, work alongside customer data science teams as a peer, and feed what you learn in the field back to our researchers to shape the model and product roadmap.

You bring 3+ years deploying ML systems in production, expert Python, strong PyTorch and scikit-learn, depth in tabular or time series ML, and cloud deployment experience (AWS, GCP, or Azure). Forward-deployed or customer-facing experience is a plus.

Sit between tabular foundation models and the hardest problems customers bring to them. You'll work with real customer data, from insurance claims to millions of card transactions to proteomic blood panels for early cancer detection, and drive what TabPFN can unlock. You'll own engagements from the first discovery call through demos and POCs to production, benchmarking rigorously against strong baselines and getting to the root cause when numbers look off.

Where out-of-the-box isn't enough, you'll push further with fine-tuning, feature engineering, ensembling, and calibration, and turn one-off wins into reusable workflows. You're also the highest-signal channel between what customers hit in the field and what the model team builds next.

You bring 3+ years of hands-on ML experience (industry, competitive ML, or open source), strong Python and PyTorch (especially transformers), and the ability to talk value with both data scientists and decision-makers. Kaggle rank, a quantitative graduate degree, or consulting and forward-deployed experience are a plus.

As a Staff Software Engineer on the Platform team, you'll design and evolve core platform services and internal APIs that power Qdrant's managed cloud offering. This role focuses on building platform primitives and abstractions, reducing complexity, and driving architectural evolution across the cloud platform.

Lead the end-to-end deployment of Reducto into customer environments, ranging from VPC to bare metal on-prem. Partner directly with enterprise IT, security, and platform teams to deploy, configure, harden, and operate Reducto inside their environments.

Lead end-to-end deployment of Reducto into customer environments with hands-on execution and direct customer exposure. Build monitoring, telemetry, and phone-home patterns, debug infrastructure issues, and codify what works into repeatable deployment patterns and automation.

Build the inference and training frameworks that make it possible to deliver results at scale. Design systems for scaling model training across multi-node, multi-GPU environments with strong reliability and observability. Explore SOTA advances in training and inference and work to apply them.

Train and deploy state-of-the-art models for parsing and interpreting unstructured data. Experiment with novel techniques to improve LLM accuracy, build data pipelines, evaluate model performance, and work directly with the founders and customers to shape product direction.

Work on features used by customers to design, build, test, and evaluate business-critical document workflows. Build interactive document viewers, data extraction workflows, and delightful experiences using Next.js, Tailwind, and Convex.

Work on Reducto's core API powering document parsing for hundreds of companies. Integrate cutting-edge LLMs, optimize document processing pipelines, and build the platform and infrastructure that makes state-of-the-art document understanding accessible at scale.

RELAI is hiring an AI Researcher to help define the future of reliable AI agents. You’ll develop novel methods for simulation, evaluation, and optimization, turning frontier AI research into production systems that improve agent behavior in real-world environments. The bar is exceptionally high, we’re looking for engineers who think in systems, operate with extreme ownership, high speed and rigor.

RELAI is hiring a Senior Full-Stack Engineer to help build the infrastructure that makes AI agents reliable in production. You’ll work across product, backend, frontend, AI infrastructure, and enterprise deployment, owning features end-to-end and shaping a category-defining platform. The bar is exceptionally high, we’re looking for engineers who think in systems, operate with extreme ownership, high speed and rigor.

As a Senior Software Engineer on Sentry's AI/ML team, you'll be directly responsible for developing the platform used by our debugging agents. This role is crucial; you will be at the forefront of integrating AI and machine learning into our core products, from issue triage and resolution to predictive analytics for application performance monitoring.

You'll build state-of-the-art agentic AI platforms to triage, debug, and solve real production issues, leveraging Sentry's novel (and massive) dataset of errors, spans, and profiles. You'll own the development of major initiatives in the AI/ML space and work alongside developers and product teams in a high-stakes, high-visibility environment.

Location: San Francisco, CA (Hybrid - in-office Mondays, Tuesdays, and Thursdays)

Salary: $150,000 - $190,000 per year

Qualifications: Minimum 5+ years of professional experience with Bachelor's degree in computer science, machine learning, or a related field. Demonstrated expertise building production-grade agentic systems and tools. Comfortable writing production quality code (we use Python and Typescript). Familiarity with deep learning frameworks (we use PyTorch) and deploying machine learning models at scale in production environments.

As a Staff Machine Learning Engineer on Sentry's AI/ML team, you'll be directly responsible for developing the models and agents used to make our product smarter and more capable. Build state-of-the-art agentic AI systems to triage, debug, and solve real production issues, leveraging Sentry's novel (and massive) dataset of errors, spans, and profiles.

Work at Sentry, we have fun. But not too much. This is still work after all. Sentry has 43 open positions across all offices (San Francisco - USA, Vienna - Austria and Toronto - Canada) and all teams and all jobs.

Design and deliver production-grade AI agents: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce.

Drive the Agent Development Life Cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way.

Partner with large enterprises and cutting-edge startups: You'll work directly with leaders at some of the world's largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in Silicon Valley, embedding AI agents across their entire business stack to drive innovation and efficiency.

Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product.

Sim is building a platform for autonomous AI agents that operate across enterprise systems. We’re looking for an engineer to own the systems behind our agent harness, including context retrieval, planning and execution, tool use, memory, failure recovery, and evaluations.

You’ll work directly with the founders to improve how our agents ingest and reason over company knowledge, diagnose failures across retrieval and execution, and use production traces and evals to improve reliability, latency, and cost.

We’re looking for someone who is mission-driven, technically exceptional, and excited about building reliable AI agent systems. New graduates are welcome; projects, internships, and independent work count.

Location: San Francisco, in person

Compensation: $190K–$250K base + 0.25%–0.4% equity

Visa sponsorship available.

In this role, you will lead our agent optimization efforts. You will design tools and mechanisms to help Temporal users build agents that are optimized for token spend and response time while maintaining result quality. Model routing is a first step, but represents the tip of the iceberg of techniques that we can apply. For example, multi-agent architecture, cache policy, and context management are all relevant. Candidates for this role should have direct experience with this problem domain.

You will work closely with other AI Foundations team members, e.g., those who focus on agentic development, maintaining a set of agents skills that lift performance of Codex, Claude Code, and similar tools for developers of Temporal applications. Other team members build ecosystem integrations or develop policy and security systems.

If you thrive on blending theory and practice, then this is the right team for you. We are an action-oriented group that loves to ship fast and solve customer problems. We also seek thorough technical grounding for our work and invest in systems and practices that foster long-term success.

Most of Temporal’s work is open source—see for yourself here: https://github.com/temporalio

Join Tessl's engineering team to build real-time AI Native workflows, tooling, and interfaces that will reshape how developers create and maintain software. You'll collaborate closely with product, design, and the wider Engineering team to bring AI Native development to life in a fast-paced, high-trust environment.

Requires 5+ years as a Software Engineer with proven experience leveraging AI coding tools and agents. Office in Kings Cross, London (3 days/week in-office).

We’re looking for a Product Marketing Manager who can take the complex world of LLM observability and make it simple, engaging, and compelling. You'll be responsible for shaping our positioning, launching new features, enabling sales, and crafting messaging that resonates with developers, product teams, and AI leaders alike.

This is a unique opportunity to join a small but mighty team that's already working with some of the world’s leading AI teams—from startups to enterprises—on one of the fastest-growing areas in AI infrastructure.

As an Enterprise Account Executive at Traversal, you’ll lead our early-stage sales efforts and build our GTM engine from the ground up. You will own the full sales cycle, from strategic prospecting to closing, while defining the playbook for our agentic observability platform.

You'll partner closely with our founders and Sales Engineering team, you will navigate complex technical evaluations and guide prospects through high-impact proof-of-concepts. We are looking for a high-ownership individual who can translate deep technical value into business outcomes for SREs, platform teams, and engineering leaders. If you have a proven track record in developer tools and thrive in high-velocity startup environments, you’ll be instrumental in scaling our AI-native infrastructure to the enterprise.

As an AI Engineer - Cloud Infrastructure on Traversal’s Infrastructure team, you’ll design, secure, and operate the core systems that power Traversal’s AI products. We already serve Fortune 50 enterprises with large-scale, multi-tenant environments, BYOC deployments, and SOC 2 Type II controls, and we’re rapidly scaling.

You’ll focus on the building blocks of our Terraform-defined infrastructure and Kubernetes environments, while supporting the complex needs of operating the highly-available, highly-resilient, and cost-efficient platform that supports the Traversal AI SRE agent.

This is a senior, high-impact role: you’ll own foundational systems, work across AWS-native infrastructure, cloud networking, Kubernetes environments, Terraform, Helm, Python, and more, shaping how enterprise AI reliability is built and scaled.

As an AI Researcher at Traversal, you'll work on improving the accuracy and speed of our agents — systems that autonomously diagnose and resolve production incidents for some of the world’s largest enterprises.

This is a hands-on, production-oriented research role. You will design experiments, run them on real data, and ship improvements. Not flag them — ship them.

You'll work end-to-end: identify a failure mode in agent reasoning, design an intervention, evaluate it against real customer traces, and get it into production. The tooling and infrastructure are in place. The research problem is hard. The feedback loop is fast. This is not a publish-papers role. It is a make-the-agent-work role – build-and-ship cutting edge AI.

As a Solutions Engineer at Traversal, you’ll help define how we engage with prospective customers, you'll guide them from initial technical discovery through successful deployment. This is a foundational, customer-facing role at the intersection of technical depth and relationship building.

You’ll collaborate with product and engineering to translate customer needs into compelling, customized pilot deployments that achieve high value for customers. You’ll work closely with our CEO, CTO, GTM and Product teams to help scale founder-led sales into a repeatable process. You’ll act as the technical voice in conversations with prospects, create resources to support go-to-market efforts, and relay insights back to the team to shape roadmap priorities.

If you thrive in high-ownership, high-velocity environments—and are excited to help define how AI-native infrastructure products are introduced and adopted—we’d love to meet you.

As a Product Engineer at Traversal, you’ll play a key role in designing and building core features powered by our AI site reliability engineer. From the user interface to the backend and infrastructure, you’ll develop product components to enable real-time incident detection, root cause analysis, and automated remediation in some of the most complex production environments. This role will focus on the ability to work across the full pipeline of our product, and someone who can have a strong product sense while also being comfortable working around AI and data processing infrastructure will be the best fit.

This is a rare opportunity to join Warp at a pivotal moment in our growth and become the first engineer focused specifically on Enterprise Security.

As a Software Engineer, Enterprise Security, you'll help define and build the security capabilities that allow the world's most security-conscious organizations to adopt Warp and agentic software development. You'll work as a product engineer—designing and shipping capabilities across identity, authorization, agent permissions, auditability, data protection, and enterprise controls—while bringing deep security expertise to the decisions we make about the product.

This is a hands-on software engineering role. You'll work directly in the Warp codebase, own major technical areas end-to-end, and partner closely with Product and GTM to understand what sophisticated enterprises need from Warp and turn those needs into great product experiences.

We're building an Applied AI team to dramatically increase productivity across Engineering, Sales, Support, and Operations as well as build out external AI functionality for our customers.

As an Applied AI Engineer, you'll design and ship production AI systems that change how WorkOS builds, sells, and supports software. You'll work on a small, high-ownership team that chooses problems based on measurable impact and moves from idea to prototype to production in days or weeks.

We're looking for an events-forward DevRel leader who thrives in the room: organizing meetups, building community, representing WorkOS publicly, and creating technical content that drives real engagement.

You'll own and scale WorkOS's developer events strategy, represent WorkOS as a public-facing technical voice, and build relationships with developer communities and influencers across the ecosystem.

As a Product Design Engineer, you'll shape how developers and AI systems interact within core developer environments. Designers at Zed work closely with engineers, prototype ideas directly in the product, and often implement parts of the interface themselves. Design is tightly integrated with engineering.