I enjoy building systems that continue to work long after the first release.

My interests lie at the intersection of backend engineering, cloud infrastructure, developer tooling, and artificial intelligence. Whether it's designing scalable APIs, securing infrastructure, building ML platforms, or creating tools that improve developer productivity, I focus on software that is reliable, maintainable, and enjoyable to use.

• 🚀 Building in public
• 🔓 Contributing to open source
• 🏗 Designing for scalability from day one
• 📊 Measuring performance instead of guessing
• 🤖 Treating AI as infrastructure—not just another feature

• 🔐 Creator of ManUp, an open-source secrets management platform
• 🚀 Creator of MLCore, a self-hosted machine learning platform
• 🏗 Built developer-first backend frameworks and CLI tooling
• 🤖 Building AI infrastructure, RAG pipelines, and LLM-powered applications
• ⚡ Experienced with distributed systems and cloud-native deployments
• 🔓 Active Open Source Maintainer

ManUp helps developers securely manage secrets across local development, CI/CD pipelines, Docker deployments, and production environments.

Instead of scattering secrets across .env files, applications fetch encrypted secrets from a centralized platform.

• 🔑 End-to-end encrypted secret storage
• 👥 Team workspaces
• 🌍 Multiple environments
• 📁 Project management
• 🔐 API Keys
• 🛡 Audit logging
• ⚡ High-performance REST API
• 🐳 Docker deployment
• 💻 Powerful CLI
• 📦 Export secrets to .env or JSON
• ▶ Run applications with injected secrets
• 🗄 PostgreSQL & PGlite support
• 🔄 Secret versioning ready
• 📈 Rate limiting & authentication

• Node.js
• TypeScript
• PostgreSQL
• PGlite
• Docker
• JWT Authentication
• Envelope Encryption
• REST APIs

🔗 Repository

https://github.com/Amanbig/ManUp

MLCore provides a unified platform for training, experimenting with, and deploying machine learning models.

• Dataset management
• Data preprocessing
• Experiment tracking
• Model training
• Prediction APIs
• Model export
• Dashboard
• Workflow management

• FastAPI
• Python
• PostgreSQL
• Async Workers
• Docker
• Modular ML Architecture

🔗 Repository

https://github.com/Amanbig/MLCore

Developer Infrastructure

Secure secrets management platform for modern development teams.

• CLI
• REST API
• Docker
• Encryption
• Team Workspaces

https://github.com/Amanbig/ManUp

Machine Learning Infrastructure

Platform for building, training, deploying, and managing ML workflows.

https://github.com/Amanbig/MLCore

Backend Framework

Developer-first framework for building scalable APIs with simplicity in mind.

https://github.com/Amanbig/runapi

Real-Time Communication

Messaging platform exploring scalable communication architecture and modern backend patterns.

https://github.com/Amanbig/chatme

• Agentic AI Systems
• Advanced Retrieval-Augmented Generation (RAG)
• Distributed Systems
• Cloud Infrastructure
• Model Serving
• ML Infrastructure
• GPU Computing
• HashiCorp Nomad
• AWS

I try to follow a few principles regardless of the technology stack.

• Keep systems simple before making them clever.
• Build software that is observable and debuggable.
• Optimize for developer experience.
• Prefer automation over manual processes.
• Security should be part of the architecture—not an afterthought.
• Design systems that can evolve without complete rewrites.

I'm always interested in collaborating on projects involving:

• 🤖 Artificial Intelligence
• ☁ Cloud Infrastructure
• 🔐 Security & Developer Tooling
• 🏗 Backend Engineering
• 🚀 Open Source
• ⚡ Distributed Systems

If you're building something exciting, feel free to reach out.