AI Engineer building context-aware agents, reliable AI systems, and the infrastructure around them.
B.Tech CSE - Data Science & Analytics at IIIT Nagpur - 2027
- Context-aware AI systems - governed context, policies, provenance, trust signals, MCP interfaces, and controlled actions.
- Stateful agents - LangGraph orchestration, tool use, persistence, human review, grounding, and failure handling.
- AI infrastructure - FastAPI/Node services, retrieval, databases, integrations, observability, CI, and evaluation harnesses.
I care as much about what happens when the model is wrong as when it is right.
| Project | What it demonstrates | Tech |
|---|---|---|
| North Star - Governed Context & Workflow System | A governed expense-operations system built around explicit, versioned context, deterministic policy boundaries, provenance, abstention, human approval, and MCP as a controlled interface. | Python, FastAPI, PostgreSQL, MCP, n8n, Metabase, Docker, GitHub Actions |
| TripBandhu - Stateful Agentic Travel Research | A travel-research agent with LangGraph supervisors, specialist tools, typed evidence, checkpoints, provider fallback, human review, and deterministic evaluation. | LangGraph, MCP, FastAPI, PostgreSQL, LangSmith, Docker, GitHub Actions |
| CortexAI - AI Developer Platform & Integration Workspace | A locally operational AI workspace with service boundaries, reusable platform primitives, persistent context, and workload-specific routing across research, coding, documents, images, vision, and PDF RAG. | Node.js, Express, LangGraph, MongoDB, Redis, Qdrant, AWS S3, React |
| Project | What it demonstrates |
|---|---|
| Internal RFP Analyst | Evidence-grounded document intelligence and retrieval agent. |
| Financial Document Intelligence | Hybrid dense + BM25 + reranking pipeline for SEC filings. |
| SifraAI | Deployed voice-enabled AI assistant platform. |
AI is part of my normal build loop, but I do not treat "the agent says it works" as completion. I use coding agents for repo exploration, implementation, tests, repetitive changes, and debugging, then verify behavior with tests, CI, traces, logs, and the running system. The architectural and product decisions stay mine.
| Area | Tools and Technologies |
|---|---|
| Agents & GenAI | LangGraph, LangChain, Model Context Protocol (MCP), RAG, tool calling, structured outputs, HITL, guardrails, agent evaluation |
| Backend & Data | Python, FastAPI, Node.js, Express, PostgreSQL, MongoDB, Redis, SQL, Qdrant |
| Reliability & Infrastructure | pytest, GitHub Actions, Docker, LangSmith, observability, provenance, failure handling |
| Integrations | AWS S3, Tavily, n8n, Metabase, Firebase |
IIIT Nagpur. B.Tech CSE - Data Science & Analytics. Graduating 2027. Currently focused on AI engineering, agentic systems, and applied AI infrastructure. Looking for a 6-month full-time internship starting September 2026.
I am open to internships and project collaborations in AI engineering, agentic systems, and applied AI infrastructure.
- Email: tg304429@gmail.com
- Portfolio: tushar-portfolio-taupe.vercel.app
- LinkedIn: linkedin.com/in/tushar-ghosh-a3355124a
- GitHub: github.com/tusharg007