I’ve spent my career turning ambiguous, high-stakes engineering problems into reliable platforms, scalable teams, and product capabilities that last. Today, I’m a Founding Engineer and Senior Director of Engineering at Empirik AI. I led our core engineering platform from its initial architecture to production and now lead a 25-person engineering organization. My scope spans backend and platform engineering, knowledge graph compilation, AI agent infrastructure, and reliability. The technical problem I care most about now is context for production AI. I don’t believe larger models alone will make agents reliable. Before an agent can reason about or change a production environment, it needs an accurate, current, and evidence-backed understanding of what exists, how everything is connected, what changed, and what could be affected next. Some of the work I’m most proud of includes: Building a continuously updated knowledge graph connecting AWS, Azure, GCP, VMware/private cloud, Kubernetes, CI/CD, applications, runtime communications, and change history. - Creating a deterministic graph-compilation system that forms relationships from provider metadata, resource lineage, and runtime evidence—not naming conventions. - Designing a governed MCP layer and provenance-first Graph-RAG architecture that give agents bounded access to dependency, blast-radius, and change-correlation intelligence. - Scaling event-driven Go/gRPC platforms to millions of events per minute, with 75% lower latency and 99.99% availability across multi-tenant environments. I am also a named inventor on two AI and knowledge-graph patent applications focused on graph compilation. Before Empirik, I built platforms at Oracle, Walmart, Rubrik, Philips, FIS, and Flipkart. Across those roles, I learned to identify durable engineering principles and turn complexity into reusable systems. I still write production Go, review graph models, and design Kubernetes and distributed-system architectures. Staying close to the technology helps me make better product, architecture, and organizational decisions. As a leader, I value explicit trade-offs, evidence over assumptions, durable engineering, and teams that move quickly without creating accidental complexity. If you are building agentic systems, infrastructure intelligence, or platforms where correctness and context genuinely matter, I would be glad to connect.