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Prabir Nandi
Staff Software Engineer specializing in cloud platforms, Kubernetes, and AI-driven engineering
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Built a production AI stylist agent for retail store associates that pulls customer loyalty, address, and purchase-history data to generate in-store product recommendations. Demonstrates hands-on experience across agent orchestration, MCP-based tool integration, Vertex AI/GCP deployment, observability, resilience patterns, and pragmatic production tradeoffs like using PostgreSQL with pgvector instead of a standalone vector database.
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Key Strengths
- Shipped a production retail AI stylist agent end-to-end
- Designed multi-agent orchestration integrating customer loyalty, address, and purchase-history data
- Built scalable cloud deployment on Vertex AI and Google Cloud for multi-store rollout
- Strong observability and monitoring mindset with actionable alerts
- Applied resilience patterns including circuit breakers, retries, and fallback handling
- Thoughtful backend security design with API gateway, Auth0, and layered request validation
- Pragmatic infrastructure tradeoffs using PostgreSQL plus pgvector instead of a separate vector database
- Used golden datasets, human review, and prompt iteration to improve agent response quality
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