

Agentic AI Engineer with 17+ years of experience building enterprise data platforms and cloud-native systems, recently specializing in autonomous AI workflows, Retrieval-Augmented Generation (RAG), and knowledge-graph driven intelligence. Strong hands-on background in Python, Spark, Neo4j, Amazon Neptune, AWS, and Azure, delivering production-grade GenAI systems that integrate LLMs with structured and unstructured enterprise data. Expert in designing MCP Server–based architectures, intelligent agent orchestration, and secure GenAI pipelines for identity resolution, analytics, and automation use cases
Promoted twice: Team Lead → Associate Manager → Engineering Manager (2017–Present)
Lead cross-functional teams of 20+ engineers delivering enterprise data, identity, and platform solutions.
Driving Agentic AI initiatives, designing MCP Server–based architectures to enable autonomous workflows and secure GenAI integrations.
Architected Identity Resolution and Knowledge Graph platforms using Python, Spark, Neo4j, and Amazon Neptune, improving data accuracy by ~40% and reducing false positives by ~30%.
Modernized legacy systems and optimized Spark pipelines, achieving ~30% performance improvement and ~35% reduction in job execution time.
Implemented SSO and centralized authorization (WSO2/Dex), improving authentication reliability and strengthening security governance.
Partner with senior leadership and product owners on roadmaps, accelerating go-to-market by ~15%.
Improved delivery predictability by ~25% through Agile optimization and engineering best practices.
Mentored team leads and engineers; delivered ~18% cost optimization through cloud governance and reusable platform components.
Progressed from Software Developer to Team Lead, contributing to enterprise backend and data-driven applications across finance and retail projects.
Designed, built, and maintained scalable services and database-driven systems with a strong focus on performance, reliability, and clean architecture.
Led small engineering teams, supporting sprint planning, code reviews, and day-to-day development activities.
Collaborated closely with business stakeholders to understand requirements and translate them into practical, maintainable technical solutions.
Built a solid foundation in distributed systems, databases, and engineering leadership, enabling a smooth transition to larger platform and cloud initiatives.
Databases: MySQL, PostgreSQL, Cassandra
Agentic AI & GenAI
Programming & Data
Graph & Knowledge Systems
Cloud & AI Platforms
Identity & Security