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Shalin Bhavsar
Mid-level Software Engineer specializing in cloud backend and distributed systems
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Built a production GenAI support agent at Amazon for FBA on-call operations, using Bedrock, Lambda, RAG, and confidence-based human fallback to safely automate ticket triage. The system materially reduced ticket volume and manual workload while improving MTTR, showing strong depth in reliable LLM agent architecture under real operational constraints.
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Key Strengths
- Shipped a production LLM support agent at Amazon for FBA on-call ticket triage
- Reduced ticket volume from ~40-50 to ~10-15 per cycle
- Cut manual workload by ~70% and improved MTTR
- Strong production-readiness focus for AI systems
- Designed hallucination mitigation with RAG grounding, abstention logic, and citation requirements
- Built confidence-based human fallback routing for safe automation
- Architected multi-step agent workflows with structured outputs and function calling
- Implemented checkpointed state management with persisted intermediate state in DynamoDB
- Designed offline/online evaluation loops and fed failures back into eval datasets
- Handled messy enterprise data with validation, standardization, permissions checks, and idempotent retries
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