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Pradeep Kolakkampadath
Director of Software Engineering
Greater St. Louis · AI Enablement · Agentic Systems
Most engineering leaders talk about AI. I build it. Then I use what I built to lead better.
I run an engineering enablement organization at Evernorth Health Services. On nights and weekends, I ship multi-agent AI systems. Persistent operating systems, governance layers, QA agents, simulation platforms. Building is not a hobby. It is how I stay ahead of what is actually possible, and how I earn the right to lead AI adoption at scale.
My next move is into AI enablement leadership. Roles where the question is how to make an entire engineering organization better with AI. Not whether to add a chatbot to the product.
01 Strengths
AI-to-production translation
Turning AI capabilities into engineering practices that teams can actually adopt.
Agentic systems design
Multi-agent architectures with memory, routing, and durable state that work across sessions.
Product-minded leadership
Balancing what's technically interesting with what's worth building for real users.
Cross-functional communication
Bridging the gap between technical depth and business understanding.
Hands-on building
Not just directing. Building. Close to the craft by choice, not circumstance.
Team development
Growing engineers who think in systems and ship with confidence.
02 How I Work
I lead by building context and trust, not by prescription. Understanding the problem matters more than committing to a direction quickly. I want my teams to have the same depth of understanding I do. I prefer structured clarity over rigid process. Clear ownership. Explicit decisions. Room for people to do their best work.
I am opinionated about quality but pragmatic about shipping. The best teams iterate fast with a clear sense of direction. I try to build that environment whether I am leading a team or building something myself.
03 What I'm Looking For
I am targeting senior engineering leadership roles at the intersection of engineering and AI enablement. Positions where I can shape how engineering teams build with AI at both the strategic and tactical level. Specific titles vary by company. The substance is what matters.
I am most interested in organizations that see AI as a capability to weave into engineering practice, not a product feature to ship. The question I want to work on is how to make an entire engineering org better with AI. Not whether to launch a chatbot.
04 Background
I've spent 20+ years in enterprise software delivery, moving from hands-on engineering into program and delivery leadership and now into platform-scale engineering enablement. Today I run an engineering enablement organization at Evernorth Health Services covering stability and resilience engineering, performance testing as an enterprise platform, test engineering and test data platforms, and delivery planning.
Along the way I've led teams through large healthcare IT programs, modernized mainframe delivery with CI/CD patterns, partnered with security on enterprise remediation posture, and pushed AI from experimentation into governed, repeatable engineering workflows. The through line is turning capabilities into products teams actually use.
In parallel I build AI systems. Multi-agent architectures, memory and routing design, durable state, and the operational patterns that make AI useful rather than impressive. The building directly informs the leadership. AI enablement that works on Tuesday morning, not just in a demo.