Senior Principal Software Engineer with 11+ years across Amazon-scale logistics, Morgan Stanley fintech and enterprise IoT — now building production RAG & AI systems on AWS.
11+ years of backend, cloud and platform engineering — measured in outcomes, not buzzwords.
I design fault-tolerant, high-throughput distributed systems — from Amazon-scale logistics platforms to post-trade validation at Morgan Stanley — and lead the teams that run them. Based in Hyderabad, India.
Production RDS fleets moved to KMS-encrypted instances — no downtime, clear rollback.
Multi-tenant platform on AWS IoT Core, Kinesis & Lambda with sub-second latency.
MTTR cut with CloudWatch, X-Ray and custom observability across services.
Best Performer (Verixo) · Best Contributor 2024 (People Tech).
Building a portfolio of retrieval-augmented systems — medical diagnosis assistant, realtime voice agent, text-to-SQL, airline support — with LangChain, FAISS, pgvector, OpenSearch and Kubernetes.
Fintech, e-commerce logistics, IoT — always the systems everything else depends on.
Architecting multi-tenant IoT platforms processing 1M+ events/day. Reusable AWS CDK modules & Helm charts that accelerate client onboarding; KMS-encrypted RDS migrations with zero downtime; 20–30% annual cloud-spend savings.
High-volume internal Amazon platform at 10,000+ RPS for global logistics & fulfillment. IoT data pipelines with CDK/SQS/Lambda/DynamoDB; 25–30% infra cost reduction; 40% MTTR cut via CloudWatch + X-Ray observability.
Post-trade validation systems for settlement & reconciliation of high-value trades. Resolved critical production issues across validation pipelines, collaborating with global teams in New York and London.
Core backend for the consensus engine powering real-time sell-side models of 1,500+ public companies; CI/CD pipelines that cut deployment time by 40%.
Highlighted chips are what I reach for daily.
Filter by what you care about — AI projects include architecture docs on GitHub.
Clinical RAG assistant combining medical documents, knowledge bases and patient metadata with an LLM — explainability snippets make every answer auditable.
Voice-first agent over WebRTC that retrieves from a Weaviate vector store mid-conversation — speech in, grounded answers out, in real time.
Natural-language questions become safe, validated SQL over live databases, with pgvector-powered schema retrieval keeping generations grounded.
Customer-support assistant for airline policies, fares and disruptions — hybrid retrieval over OpenSearch with guardrailed responses.
Enterprise IoT data platform on AWS IoT Core, Kinesis and Lambda — sub-second processing, tenant isolation, 99.99% uptime.
Java microservices behind Amazon's global logistics & fulfillment operations — fault-tolerant, horizontally scaled, continuously deployed.
Repeatable framework for migrating live RDS databases to KMS-encrypted instances — zero downtime, automated verification, instant rollback.
Settlement and reconciliation pipelines at Morgan Stanley — data integrity, compliance and stability for mission-critical trade flows.
Hiring for a senior IC who owns outcomes end-to-end? Or want to talk distributed systems and RAG? My inbox is open.