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Akhil Chippalthurthy
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and predictive analytics
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About
GenAI/LLM engineer who architected and deployed a production RAG “research assistant” for JPMorgan Chase’s regulatory compliance team, focused on safety-critical behavior (mandatory citations, refusal when evidence is missing). Deep hands-on experience with LlamaIndex, Pinecone, Hugging Face embeddings, LangGraph agent workflows, and metric-driven evaluation (golden sets, TruLens), including a reported 28% relevancy lift via cross-encoder re-ranking.
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Key Strengths
- Built and deployed production RAG system for regulatory compliance research at JPMorgan Chase
- Designed safety-critical LLM workflow with mandatory citations and explicit “not in context” behavior to reduce hallucination risk
- Improved answer relevancy by 28% using cross-encoder re-ranking over initial vector retrieval
- Architected modular, swappable GenAI stack to adapt to evolving LLM components
- Strong agentic orchestration skills (stateful LangGraph workflows with self-correction and human approval gates)
- Rigorous evaluation approach: golden datasets, adversarial/jailbreak testing, and metric-driven iteration (TruLens/LLM-as-judge)
- Effective collaboration with non-technical legal/compliance stakeholders by reframing metrics around auditability and trust (attribution UI, live break-testing workshops)
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