Staff Platform Engineer & Solutions Architect with nearly 16 years of experience architecting and delivering enterprise-grade full-stack, cloud-native, data, and AI platforms, including 5+ years of production Generative AI implementation.
Spearheaded Agentic AI, Multi-Agent, RAG, and LLM architectures leveraging AWS Bedrock, LangGraph, LangChain, OpenAI, Claude, and hybrid search, translating complex enterprise challenges into scalable intelligent solutions. Engineered large-scale data ecosystems using Python, Spark, Airflow, Kafka, AWS Glue, and Athena, processing cloud events daily across multiple AWS accounts to power analytics, automation, and AI-driven decision intelligence.
Recognized for end-to-end architecture ownership, customer-embedded engineering, executive stakeholder engagement, and reusable AI/cloud accelerators, consistently bridging business strategy, technology architecture, and production execution across complex enterprise environments.
Key Career Highlights
- Enterprise GenAI & Agentic AI: Architected enterprise-grade GenAI, Agentic AI, RAG and multi-agent platforms delivering 75% lower manual effort and 40% faster turnaround.
- Large-Scale Data & Telemetry: Architected data and operational platforms processing 15M+ cloud events daily across 1,700+ AWS accounts with Spark, Airflow, Kafka, Glue, EMR, Athena and GenAI.
- Operational Reliability & LLMOps: Established LLMOps/MLOps, evaluation, monitoring and reliability patterns contributing to 99.9% availability, 30% MTTR reduction, and 20% lower cloud costs.
- Reusable Accelerators: Built reusable architecture patterns and AI/cloud accelerators reducing new AI use-case build effort by ~35%.