Senior Principal Agentic Engineer

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve.

This is hard, urgent, selfless work-but it's work worth doing. If you're driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

** About the technology organization*
* Technology at Lilly builds and operates mission-critical digital products and platforms that support the discovery, development, and delivery of medicines that make life better for people around the world. Our teams operate in highly regulated, high-availability environments, where operational excellence, reliability, and quality are non-negotiable.

Within Technology at Lilly, the Digital Core organization applies a product, platform, and reliability-first mindset, ensuring that operational capabilities scale sustainably across the enterprise.

** About the Team*
* Technology at Lilly builds and maintains capabilities using pioneering technologies like the most prominent tech companies. What differentiates Lilly IT is that we redefine what's possible through tech to advance our purpose, creating medicines that make life better for people around the world, including data-driven drug discovery, connected clinical trials, resilient enterprise platforms, and intelligent digital operations. We hire the best technology professionals from a variety of backgrounds, so they can bring an assortment of knowledge, skills, and diverse thinking to deliver creative solutions in every area of our business.

The Digital Core team leads Lilly's transformation into the Digital and AI era. They inspire digitally empowered teams to new ways of working and accelerate innovation and agility. This team powers and advances the entire company by building and maintaining world-class technology capabilities and platforms.

The Reliability Engineering team is the engineering-first function that owns the stability, observability, and operational quality of a multi-application production estate. It operates in close partnership with the engineering team that builds the agentic automation platform, and is in active transition from human-executed operations to engineering-led, agent-assisted reliability.

** Role summary*
* You own the agentic resolution platform end to end - both the cloud-native substrate it runs on and the intelligent agents that run on top of it. From Kubernetes, CI/CD, and observability through agent runtime, LLM patterns, retrieval, evaluation, and human-in-the-loop boundaries, you write the production code, design the architecture, and set the engineering bar that lets automation deflect routine operational work before it ever reaches a human.

This is a senior individual-contributor role that is both strategic and deeply hands-on. You ship production platform services and agentic capabilities, make the build-vs-buy calls on tooling and model access, and partner with the senior architect on the patterns that scale. Success is measured by rising deflection, sustained toil reduction, platform availability and developer velocity, and the ability to scale agentic intelligence through systems and people - not individual effort.

** What you'll be doing*
* *
* 1) Agentic resolution platform - intake to action*
* + Architect the agentic resolution platform end to end: intake, classification, action execution, verification, and human-in-the-loop fallback.

+ Build the agent runtime and orchestration layer: agent state and memory, tool integration, multi-agent coordination patterns, and confidence-thresholded handoffs to humans.

+ Define agent-decision observability, audit-ready posture, and the data contracts that let the platform consume durable fixes from upstream engineering teams.

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* 2) LLM application patterns, knowledge, and evaluation rigor*
* + Design production LLM patterns: prompt engineering, retrieval-augmented generation (RAG), structured outputs, multi-model routing, and hybrid retrieval over the knowledge corpus.

+ Own the knowledge-base strategy as a compounding deflection lever - every resolved incident becomes training data and structured retrieval input for future…