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Rajat SinhaRS
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Rajat Sinha

@rajatsinha

I build production-oriented RAG and multi-agent AI systems that improve retrieval speed, latency, and research workflows.

India
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At Tata Consultancy Services, I build production-oriented RAG systems that ground answers in internal documents using LangChain, ChromaDB, hybrid retrieval, and metadata filtering.

I've reduced knowledge search time by 30% and lowered average LLM latency from 2.1 seconds to 1.3 seconds through inference profiling and semantic query caching.

I also engineered LangGraph-based multi-agent workflows for planning, retrieval, and generation, cutting research turnaround time by 25%. My AI-Orchestrated Research System uses eight agents to turn 1–2 hours of research into citation-backed reports in under 30 minutes.

Earlier, I built React interfaces and REST APIs at Tata Consultancy Services, reducing UI latency by 20%. I bring Python, JavaScript, SQL, and full-stack delivery experience to AI-powered products, including ResumeOS, an AI resume optimization platform.

Experience

Work history, roles, and key accomplishments

Education

Degrees, certifications, and relevant coursework

Chandigarh University logoCU

Chandigarh University

Bachelor of Engineering, Computer Science

2020 - 2024

Grade: 7.54/10

Pursued a Bachelor of Engineering in Computer Science, achieving a CGPA of 7.54/10.

Harvard University logoHU

Harvard University

CS50: Introduction to Computer Science, Computer Science

Completed CS50: Introduction to Computer Science, covering fundamental computer science concepts and programming.

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