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Sourabrata Samanta
Intern Data Scientist specializing in AI, analytics, and cloud data engineering
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About
Built a production multimodal LLM-based vendor risk assessment platform that ingests SOC reports and other documents, uses a strict RAG pipeline with grounded evidence (page/paragraph citations), and dramatically reduces analyst review time. Experienced with LangGraph/LangChain/AutoGen for stateful, fault-tolerant agent workflows, and emphasizes reliability (schema validation, guardrails) plus low-latency delivery (~1–2s) through hybrid retrieval, reranking, caching, and model tiering.
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Key Strengths
- Built and deployed an end-to-end LLM vendor risk assessment system automating SOC report review and control scoring
- Strong production focus: strict I/O contracts, failure-mode planning, deterministic workflow decomposition
- Reliability engineering for LLMs (evidence-only prompting, validation layers, rule-based fallbacks)
- High-quality retrieval design (hybrid retrieval + reranking) to improve grounding and accuracy
- Performance optimization to achieve ~1–2 second response times (caching, model tiering)
- Effective collaboration with non-technical stakeholders; translates workflows into usable AI tools and iterates on trust/clarity
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