Full Stack Developer → AI/GenAI | RAG Systems · LLM Integration · AI Applications
4+ years building enterprise platforms at Tecnotree. Now shipping AI-native tools with RAG, vector search, and LLM integration — from browser extensions to full-stack SaaS.
- AI Applications → RAG pipelines, LLM integration, vector search, agentic systems
- Full Stack Products → React, Next.js, TypeScript, Python/FastAPI, PostgreSQL
- Chrome Extensions → Manifest V3, background workers, side panels
AskMyDocs — Full Stack RAG Document Q&A SaaS
Upload PDFs, ask questions, get grounded answers — powered by a production RAG pipeline.
- PDF ingestion → Gemini embeddings (768-dim) → pgvector cosine similarity → Gemini LLM synthesis
- Next.js 15 · FastAPI · PostgreSQL + pgvector · AWS S3 · AWS EC2 · Docker · JWT · Neon.tech
- Live on Vercel + AWS EC2
| Project | What it does | Stack |
|---|---|---|
| DeepTrail | AI research knowledge graph from browser activity | Chrome MV3, React 18, FastAPI, pgvector, Groq/Llama 3, React Flow |
| Lumen AI | Real-time webpage analysis via LLM with BYOK privacy | Chrome MV3, JavaScript, Groq/Llama 3.1 |
Frontend → React, Next.js, TypeScript, Tailwind, shadcn/ui, Chrome Extensions
Backend → Python, FastAPI, Node.js, PostgreSQL, pgvector, Redis
AI/GenAI → RAG, Embeddings, LLM APIs (Groq/Gemini/OpenAI), Agentic Systems, LangChain
Infra → Docker, GitLab CI/CD, GitHub Actions, Render, Neon.tech
AI Tools → Claude Code, Cursor, GitHub Copilot, v0
Open to Full Stack, GenAI, or hybrid roles — remote preferred.