const zeeshan = {
role: "Full Stack Software Engineer",
focus: ["Backend Systems", "AI-Powered Products", "Cloud Automation"],
stack: ["TypeScript", "Node.js", "Next.js", "Python", "AWS"],
building: "Practical AI tools that ship to production",
open_to: "EU software engineering & AI-integrated product roles",
};I build production web platforms, APIs, and dashboards — currently going deeper into backend engineering and applied LLM workflows.
| Production dashboards | Internal tools for ops, analytics, and decision support |
| Backend APIs & services | Node.js / Express, REST & GraphQL, async workflows |
| Full-stack platforms | React, Next.js, modern deployment & DX tooling |
| AI / LLM integrations | Assistants, structured extraction, agentic workflows |
| Cloud automation | AWS Lambda, Amplify, CloudWatch, Docker, CI/CD |
| Observability | Logging, error tracking, alerting, feedback loops |
- Going deeper into backend + AI engineering
- Building applied LLM workflows for real business problems
- Shipping AI-powered business tools end-to-end
- Sharpening cloud deployment & automation practice
- Growing portfolio depth with engineered, finished projects
| Layer | Technologies |
|---|---|
| Languages | TypeScript · JavaScript · Python |
| Frontend | React · Next.js · Vite · Tailwind CSS |
| Backend | Node.js · Express · REST · GraphQL · Socket.IO |
| Databases | MongoDB · PostgreSQL · MySQL · Redis · Firebase |
| Cloud & DevOps | AWS (Lambda · Amplify · CloudWatch) · Docker · GitHub Actions |
| AI & Automation | OpenAI API · LangChain · AI Agents · NLP Pipelines · Prompt Engineering |
- AI-powered business management — inventory, orders, logistics, and customer workflows with AI-assisted automation in the operational layer.
- Production dashboards & analytics — operational visibility, reporting, and real-time decision support across multiple domains.
- Backend & platform engineering — scalable APIs, workflow services, cloud integrations, and automation pipelines under real load.
- Observability & automation — logging, error tracking, and alerting that shorten the loop from incident to fix.
- AI workflow integrations — structured extraction, validation, and assistants embedded into existing product surfaces.
Product-first. Boring, predictable architecture beats clever abstractions. Code is read more than written, so I optimize for the next reader. I care about the messy parts — auth, edge cases, retries, observability — because that's the difference between a demo and a system. Ship small, learn in production, iterate.
Open to conversations around software engineering, AI-powered products, backend systems, and practical automation. If you're building something where engineering quality and applied AI matter — let's talk.