Mohit Rajpal
@mohitrajpal
I build production multi-agent RAG systems, LLM guardrails, and scalable AI services.
What I'm looking for
At Capgemini, I build production multi-agent RAG pipelines and enterprise LLM systems using LangGraph, LangChain, FastAPI, and Google Gemini. My work improved document retrieval accuracy by approximately 40% and reduced hallucination rates by approximately 30%.
I designed an LLM security guardrails gateway that blocks prompt injection, PII leakage, and adversarial attacks. I secured model access with JWT-based RBAC and rate limiting for more than 500 concurrent enterprise users.
I also develop async FastAPI microservices, improve AI observability through structured logging and distributed tracing, and ship Docker/Kubernetes deployments through Jenkins CI/CD quality gates.
Outside production work, I've built agentic research, guardrails, and query-routing systems using Weaviate, ChromaDB, DeBERTa, Redis, and Google Gemini.
Experience
Work history, roles, and key accomplishments
Software Engineer – GenAI
Sep 2024 - Present (1 year 11 months)
Built production multi-agent RAG pipelines using LangGraph and Google Gemini, improving retrieval accuracy by ~40% and cutting hallucination rates by ~30%. Designed an LLM security guardrails gateway in FastAPI and shipped Jenkins CI/CD pipelines with Ragas quality gates for Kubernetes deployments.
Education
Degrees, certifications, and relevant coursework
G.H. Raisoni College of Engineering
Bachelor of Technology, Computer Science and Engineering
Pursued a Bachelor of Technology in Computer Science and Engineering, graduating in 2024.
Availability
Location
Authorized to work in
Job categories
Skills
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