Strategic AI leader with 4+ years of experience designing production-ready GenAI platforms and cloud-native systems. Expert in bridging the gap between complex technical infrastructure and business product roadmaps.
As a Senior AI & Cloud Solutions Architect, I specialize in designing and implementing enterprise-scale AI systems that bridge the gap between cutting-edge technology and practical business solutions.
My expertise spans across:
Selected technical projects and implementations
Production-grade Retrieval-Augmented Generation with AWS Bedrock and OpenSearch, serving thousands of users
Comprehensive AI agent evaluation suite with metrics for accuracy, reasoning consistency, and tool-calling reliability
Asynchronous AI-powered system processing 10,000+ monthly emails with automated response generation
Automated evaluation for AI-generated content with brand compliance and legal regulation checks
High-fidelity HTML-based translation system with LLM-powered semantic accuracy
On-prem to AWS migration for mission-critical systems (Oracle DB, AD, EFS) with seamless cutover
Cost-efficient data ingestion pipeline using Lambda, Glue, and Kinesis for pharma insights
Serverless label generation with automated print workflows for automotive production lines
Deep dives into AI, cloud architecture, and production-grade system design
Building a production-ready Retrieval-Augmented Generation system requires more than just connecting an LLM to a vector database. This article shares architectural decisions, challenges, and lessons learned from deploying enterprise-scale RAG solutions.
Read Full Article →How do you measure AI agent performance in production? Exploring metrics for accuracy, consistency, reasoning quality, and tool-calling reliability.
Practical strategies for operating Large Language Models at scale—from prompt versioning to cost optimization and observability.
Migrating mission-critical systems to the cloud without downtime. Strategies, gotchas, and architectural patterns that worked.