Agentic AI & autonomous servicing
LLM-driven agents and orchestration patterns that act on customer intent — with guardrails, evaluation, and human-in-the-loop controls built in from day one.
IEEE Senior Member, published AI researcher, and engineering leader with 19+ years building enterprise platforms, search and knowledge systems, and AI‑enabled customer experiences across the fintech stack.
My work sits at the intersection of agentic AI, knowledge systems, and fintech platform engineering — designed for environments where accuracy, accountability, and operational reliability are non-negotiable.
LLM-driven agents and orchestration patterns that act on customer intent — with guardrails, evaluation, and human-in-the-loop controls built in from day one.
Domain knowledge models that connect products, content, intents, and customers — fueling retrieval, reasoning, and recommendation across the experience.
BERT, embedding, and graph-aware retrieval — engineered for financial language, regional nuance, and conversational query patterns.
Behavioral signals and predictive models that anticipate friction, surface the next-best action, and personalize the servicing experience.
Evaluation harnesses, governance, monitoring, and human-in-the-loop patterns that make generative AI safe to ship in regulated, high-stakes contexts.
Scalable Java/Spring, Node.js, and cloud-native systems — modernizing legacy stacks into composable, AI-ready platforms without breaking the business.
Multi-agent orchestration, tool use, planning, and reflection — paired with evaluation, escalation, and policy controls suited to regulated environments.
LLM-grounded summarization, intent understanding, and conversational servicing — with retrieval, citations, and fallbacks rather than naked prompting.
Product knowledge graphs, taxonomies, and content models that make domain semantics first-class — so search, recommendation, and agents share one source of truth.
From Lucene-era relevance tuning to embedding and graph-aware retrieval — treating search as a continuously evaluated product, not a one-time integration.
Bootstrapping recommendations when behavioral signal is thin — including LLM-assisted training data generation and synthetic intent modeling.
Building high-trust engineering teams, architecting roadmaps that survive contact with reality, and translating AI ambition into shippable, measurable platforms.
AI-enabled customer experience, autonomous servicing & platform engineering
Customer experience platforms, knowledge systems & self-service
Knowledge platform, search & self-service engineering
Enterprise software delivery for energy, financial services & insurance clients
Enterprise web, rich-internet & e-commerce platforms
Six independent research papers published in peer-reviewed journals — focused on the production-grade challenges of bringing AI to customer-facing fintech and commerce systems.
Featured interviews and editorial contributions on the practical and strategic dimensions of AI in regulated, customer-facing environments.
A deep dive into how behavioral intelligence is reshaping customer experience in financial services — from intent modeling to proactive servicing at scale.
Why the shift from AI tools to AI agents demands a new architecture for trust, governance, and human oversight in enterprise environments.
Examining the practical path from generative AI experiments to production-grade systems that create measurable business outcomes in fintech.
How responsible AI design enables customer-centric prediction — without compromising on privacy, fairness, or regulatory compliance.
An elevation level reserved for engineers with significant professional achievement — fewer than 10% of IEEE members hold this grade. Active across IEEE Computer Society, Control Systems Society, Signal Processing Society, and Technology and Engineering Management Society.
Invited industry keynote speaker at the IEEE Computing Conference on Intelligent Computing (CCIC) 2026 — contributing research and perspective on AI systems, agentic design, and trustworthy AI.
Six peer-reviewed publications on semantic search, product knowledge graphs, recommendation systems, LLMs, NFTs in commerce, and trustworthy AI frameworks — spanning 2019 to 2023.
Multiple SPOT awards and team performance recognitions across engineering delivery milestones. PayPal Austin Hackathon Bounty Winner, 2018.
Harmony Public Schools District Science Fair judge (2020) — evaluating student STEM research and supporting the next generation of engineers and scientists.
CSC Chairman's Technical Excellence Award nominee. Covansys PRIDE Recognition (2006, 2007) and CORE Excellence Award for innovation and delivery execution.
Post-Graduate Program in Cloud Computing, The University of Texas at Austin. MCA and B.Sc. Computer Science, Bharathiar University, India.
AI Agentic Design Patterns with AutoGen (DeepLearning.AI) · Certified Product Manager (Product School) · Six Sigma Green Belt · Sun Certified Java Programmer · IBM Certified Developer & Database Associate.
Open to senior AI engineering leadership conversations — including Director of AI Engineering, Head of AI Platform, Director of Agentic AI, and FinTech AI engineering leadership roles. The fastest path is LinkedIn.