Gagan Jain

AI / LLM Engineer

Jaipur, India (Open to Relocation) · +91 95872 55792 · gagan.jain.se@gmail.com

Professional Summary

AI Engineer focused on production-grade GenAI systems: agentic AI orchestration, RAG pipelines, LLM fine-tuning (QLoRA/LoRA), MCP tooling, and local-first LLM deployment. Author of NexusAOS, a governance-first, event-sourced AI operating environment written in Rust (12 workspace crates, 981 tests, full CI/CD) with provider-agnostic LLM streaming (OpenAI/Anthropic), policy-enforced agent actions, and terminal/SSH integration. Strong Python + Rust foundation with end-to-end deployment: Docker, GitHub Actions, observability, and AI governance.

Technical Skills

AI / LLM

LLM Integration, RAG Pipelines, Agentic AI Frameworks, Prompt Engineering, Context Engineering, Multi-Agent Systems, Tool-Using Agents, Fine-tuning (QLoRA/LoRA), MCP / Tool Protocols, LangChain / LlamaIndex, Vector Databases, AI Governance

LLM Ops

Evaluation & Observability, Local LLM Deployment, OpenAI / Anthropic APIs, Embeddings, Structured Outputs / Function Calling, LiteLLM / Model Routing, Streaming Responses, NLP, Ollama

Languages

Python, TypeScript, JavaScript, Rust, C++, C, PHP, HTML/CSS

Backend & APIs

Flask, FastAPI, Node.js, Express, Laravel, Axum (Rust), REST APIs, WebSockets

Databases & DevOps

MySQL, MongoDB, Redis, SQLite, Supabase, Docker, GitHub Actions, Nginx, Gunicorn, Prometheus, Linux

Frontend & Vision

React, React Native, Next.js, Tailwind CSS, Bootstrap, Monaco Editor, YOLO, OpenCV, Computer Vision

Projects

NexusAOS

AI/AGENTIC

Governance-first, event-sourced AI operating environment in Rust — 12 workspace crates, 981 tests, provider-agnostic LLM streaming.

  • Designed a governance-first, event-sourced AI OS in Rust: 12 workspace crates, 981 passing tests, 0 clippy warnings, full GitHub Actions CI/CD
  • Built a policy-enforced agent kernel where LLMs propose actions and the kernel validates and records every state change in an append-only audit trail
  • Implemented a provider-agnostic LLM layer with OpenAI-compatible and Anthropic streaming, LiteLLM routing, and local-first inference that runs fully offline
  • Delivered native terminal emulation (PTY + VT100), SSH multiplexing, a secrets vault, and four interfaces: CLI, TUI, GUI, RPC

nexus-kernel

AI/AGENTIC

Companion repo to NexusAOS — the alpha-track sibling of the same 12-crate Rust workspace, focused on the microkernel layer (event-sourced governance, provider-swappable model interface).

  • Companion to NexusAOS: shares the same 12-crate Rust workspace and its 981-test suite (tracked under NexusAOS)
  • Implemented event-sourced append-only audit trail, policy engine with trust tiers, and provider-swappable model interface
  • Integrated OpenAI-compatible and Anthropic streaming with real-time token streaming into TUI/GUI
  • Delivered native terminal emulation (PTY + VT100 + Zig parser), SSH multiplexing, and multi-interface CLI/TUI/GUI/RPC

SeshaOS

AI/AGENTIC

NexusAOS v2 — governance-first, local-first AI OS with specialist local models and LiteLLM-compatible routing.

  • Architected specialist model stack: Gemma 4 12B (Planner), Qwen3-Coder 30B (Implementation), Qwen3.5 9B (Vision)
  • Designed kernel-centric governance where models propose actions and the kernel validates/records every state change
  • Built a LiteLLM-compatible proxy for NVIDIA NIM and other model providers
  • Maintained event-sourced architecture with reversible, permissioned actions and offline-first execution

Vyākṛti

FLAGSHIP

Sanskrit-oriented programming language with complete compiler pipeline and browser-based IDE. 123 tests.

  • Complete compiler pipeline: lexer → parser → type checker → bytecode compiler — all built from scratch in Rust
  • Browser-based IDE with React, Monaco Editor, syntax highlighting, autocomplete, and diagnostics
  • Rust (axum) backend with compile, REPL, LSP, and file management endpoints via REST + WebSocket
  • 123 tests covering the full pipeline, including a self-hosting corpus

RAG Service — Production RAG + Vector Search

Gen AI

Production RAG API service: hybrid retrieval (vector + keyword), embeddings, reranking-ready, and an LLM-as-judge eval harness.

  • Built a FastAPI RAG service with hybrid retrieval (dense embeddings + BM25 keyword, merged via Reciprocal Rank Fusion) over ChromaDB
  • Implemented chunking strategies (recursive, semantic), embedding pipelines, and an /ask endpoint that streams grounded answers with citations
  • Shipped LLM-as-judge evaluation harness (faithfulness, answer relevance, correctness) with golden-set CI gate and RAGAS-style reports
  • Containerized with Docker Compose; OpenAI-compatible LLM interface with local-first fallback

LLM Eval Harness

Gen AI

Reusable LLM evaluation harness: golden-set YAML, LLM-as-judge metrics, offline heuristic fallbacks, and CI-ready reports.

  • Built a golden-set-driven evaluation harness with faithfulness, answer-relevance, and correctness metrics (LLM-as-judge + lexical fallbacks)
  • Added offline heuristic scorers so evals run in CI without API keys; JSON + Markdown reports for regression tracking
  • Designed golden-set YAML format (question, golden answer, context) and a CLI: python -m eval_harness --golden-set ...
  • Containerized and CI-ready; used to gate the RAG service pipeline

AIM — Attendance Information Manager

PRODUCTION-READY

Production-grade Flask + MySQL platform with Argon2id auth, Prometheus monitoring, and CI/CD.

  • Production-grade Flask + MySQL platform with Argon2id auth, CSRF protection, brute-force lockout, breached-password scanning, JWT sessions, and strict CSP/HSTS headers
  • Deployed Prometheus metrics, structured JSON logging, Chart.js analytics, FullCalendar scheduling, Docker Compose, and GitHub Actions CI/CD; 101 automated pytest tests

FWRS — Food Waste Reduction System

PRODUCTION-READY

Optimizes surplus-food allocation to NGOs with a 3-stage lexicographic linear program (fairness → priority → cost) and expiry-aware routing.

  • Built a 3-stage lexicographic LP solver (fairness → priority → cost) to allocate surplus food to NGOs while minimizing waste
  • Added expiry-aware routing that penalizes allocations where travel time exceeds food shelf life
  • Integrated Folium/Leaflet interactive maps with animated routes, heatmaps, and priority-colored markers
  • Shipped a Flask web dashboard plus a desktop Tkinter GUI with charts and CSV export

Experience

Industry 5.0 Industrial Automation Trainee

CodenPlay Robotics

Aug – Nov 2025

VIT Vellore / Online

  • Built and debugged PLC automation logic (ladder logic, structured text) in CODESYS
  • Simulated industrial process workflows in Factory I/O
  • Implemented flow-based control/integration in Node-RED
  • Covered HMI design, industrial communication, process monitoring, and the debugging→testing→deployment workflow

Education

Vellore Institute of Technology, Vellore

B.Tech in Computer Science and Engineering

CGPA: 7.7 / 10.0 | Relevant Coursework: Data Structures & Algorithms, Operating Systems, Database Systems, Computer Networks, Web Technologies, Artificial Intelligence, Machine Learning

Graduated 2025