Building AI systems that actually ship.
I design and build AI agents, LLM applications, and the backend infrastructure that puts them into production — not just proof-of-concepts.
Building at the intersection of AI research and production engineering.
I'm a Computer Science & Engineering student building toward AI agent engineering — the kind of AI system that goes beyond a chat window, calling tools, retrieving real data, and connecting to production infrastructure through protocols like MCP.
I've already shipped six end-to-end AI systems on my own — a multi-user RAG document platform, a RAG-based customer support assistant, an AI agent for construction planning, a tool that analyzes agents and generates MCP configs, an NLP triage API, and a voice assistant. Most of them are live in production today, not just running on my laptop.
I care about the full lifecycle of a product: designing the architecture, writing the backend and APIs, wiring up the database, deploying to the cloud, and debugging it when it breaks in production. I don't stop at a working demo — I focus on AI agents, MCP, and the backend/API layer that makes those systems reliable and shippable.
FOCUS AREAS
- AI Agents
- MCP (Model Context Protocol)
- LLM Applications
- Backend & APIs
- Cloud Deployment
- Full-Stack Development
Where I've put this to work.
Professional roles and the responsibilities and technologies behind them.
Web Developer Intern
Jan 2025 — Feb 2025Built responsive web interfaces and shipped UI components under production-quality standards within tight sprint cycles.
- ▸Built responsive web interfaces using HTML, CSS, and JavaScript
- ▸Shipped multiple UI components and pages within tight sprint cycles
- ▸Worked with client-facing deliverables under production code quality standards
Things I've shipped.
Every project here went from an idea to a deployed, working system — not just a repo. Click through for the full build breakdown.
Beyond the chatbot: agents that call tools and touch real data.
A quick look at how an AI agent request actually flows through a production system — from the user's request to a grounded response.
Technical stack.
Tools and technologies I actually use — organized by where they sit in the stack.
AI / LLM
BACKEND
FRONTEND
DATABASE
CLOUD / DEVOPS
TOOLS
Education & certifications.
EDUCATION
- B.E. Computer Science & EngineeringProf. Ram Meghe College of Engineering & Management2023 — Present (Expected 2027) · Amravati, India
Specializing in AI/ML alongside core computer science fundamentals, while independently building and deploying production AI systems.
Live from GitHub.
Public activity, pulled live — not a static snapshot.
Dev Patmase
@mrdevpatmase
AI/ML Dev | NLP & Voice AI Enthusiast Building intelligent systems with Python, Scikit-learn & LLMs 📍 Amravati, Maharashtra | 🎓 LangChain, Transformes, RAG
Have a problem worth building?
I'm open to AI/ML and backend engineering roles, freelance builds, and interesting technical problems. If you're working on something that needs an agent, an API, or a system that actually ships — let's talk.