Technical Lead with 9 years of experience — LangGraph, Azure OpenAI, RAG pipelines, and cloud architecture at enterprise scale.
Years of Experience
I started as a full-stack developer in 2017, building MEAN stack applications — work management platforms, news portals, hospital management systems. The foundation was strong: clean architecture, performance optimization, and the discipline of shipping production code that real users depend on.
At Geotech Infoservices, I grew beyond engineering. As Frontend Practice Area Lead, I built and governed a centralized design system using Angular, React, and Storybook across multiple teams. I architected a multi-tenant InsurTech platform serving 800+ enterprise tenants and 20,000+ users — the kind of scale that teaches you what "production-grade" actually means.
The GenAI inflection point changed everything. I pivoted hard into AI architecture from the ground up — not as a side interest, but as the primary focus. Today I specialize in multi-agent orchestration using LangGraph and Azure OpenAI, RAG pipelines with vector databases like Qdrant and OpenSearch, and agentic workflows on AWS Bedrock. The systems I build aren't demos — they serve real enterprises, drive 40,000–50,000 additional weekly orders, and compress two-week manual processes into six-hour automated workflows.
That journey from full-stack engineer to AI Solutions Architect — through frontend leadership, platform architecture, and deep AI systems work — is what makes my approach different. I don't just build models. I build systems that solve business problems at scale.
Production multi-agent systems with complex state graphs and human-in-the-loop workflows.
Enterprise-grade LLM deployments with cost governance, model routing, and fallback strategies.
Federated retrieval architectures using Qdrant, OpenSearch, and hybrid search strategies.
Evaluation frameworks, observability, prompt management, and CI/CD for AI systems.
High-performance async APIs, Docker-based microservices, and cloud-native design patterns.