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Polam Srija
Mid-level AI/ML Engineer specializing in Generative AI and FinTech
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AI Engineer with hands-on ownership of a production multi-agent RAG platform in financial services, spanning experimentation, architecture, deployment, monitoring, and iterative optimization. Stands out for measurable impact: 35% retrieval relevance improvement and nearly 50% reduction in manual operational analysis effort, plus strong experience making enterprise LLM systems safer and more reliable in production.
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Key Strengths
- Owned production GenAI system end-to-end from experimentation through deployment and monitoring
- Built multi-agent RAG platform for financial services operational analysis
- Improved retrieval relevance by 35% using hybrid retrieval and reranking
- Reduced manual operational analysis effort by nearly 50%
- Strong grounding and hallucination mitigation in enterprise LLM systems
- Balanced latency, cost, quality, and safety tradeoffs in production AI systems
- Iterative production optimization using chunking, caching, thresholds, and metadata filtering
- Designed reusable Python/FastAPI services and shared AI workflow components for multiple teams
- Improved team velocity and reduced duplicate engineering effort through modular platform design
- Established testing, CI/CD, logging, and monitoring practices for reliability
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