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Sumasri Jasti
Mid-level GenAI Engineer specializing in LLM agents and RAG systems
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Designed and deployed a production LLM agent platform at the National Institutes of Health to reduce time spent searching fragmented internal documentation, combining RAG grounding with multi-step tool-calling workflows and integration into legacy services via inference APIs. Emphasizes production-grade reliability through automated evaluation on real queries, guardrails/safe-failure behaviors, and ongoing A/B testing and monitoring, and has experience translating non-technical stakeholder goals into measurable success metrics.
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Key Strengths
- Built and deployed an end-to-end production LLM agent system at NIH
- Strong RAG grounding and safety approach for sensitive/internal documents
- Performance optimization via distillation and domain fine-tuning to balance accuracy and latency
- Production reliability mindset: defined metrics (accuracy/latency/failure rates) and automated eval on real queries
- Robust guardrails and safe-failure design to prevent ungrounded outputs
- Designs modular agent workflows with independent testability and edge-case coverage
- Continuous improvement using monitoring plus controlled A/B testing of prompts and model choices
- Bridges non-technical stakeholder needs into measurable requirements and iterative prototypes
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