Senior Principal Agentic Platform Engineer

BioSpace; Indianapolis (IN); On-site; USD 129,000 - 231,000; Full time

Job summary

Lilly in Indianapolis, Indiana, seeks a senior platform engineer to own the agentic resolution platform end to end, including the cloud-native substrate and intelligent agents. You will write production code, design architecture, and set engineering standards to deflect routine operational work.

This senior IC role blends strategy with hands-on delivery, focusing on reliability, developer velocity, and scalable agentic intelligence across cloud-native platforms in regulated environments.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related technical engineering discipline.
• 7+ years of progressive technology experience with substantial hands-on architecture and delivery of automation, AIOps, agentic systems, or cloud-native platforms at enterprise scale.
• Demonstrated experience designing, building, and deploying agentic AI solutions in production environments, including agent runtimes, multi-agent orchestration, tool integration, and memory-state management, with hands-on implementation using at least one major framework (LangGraph, LangChain, LlamaIndex, or MCP).
• Production experience with LLM application patterns: prompt engineering, retrieval-augmented generation (RAG), structured outputs, and multi-model routing.
• Demonstrated experience designing, deploying, and supporting cloud-native solutions in production environments, including Kubernetes (EKS or equivalent), containerized workloads, infrastructure as code using Terraform, and implementation of AI services on at least one major cloud platform (AWS Bedrock/SageMaker, Azure AI Foundry, or Vertex AI).
• Demonstrated experience designing, developing, and deploying production platform services and engineering tools, with hands-on software development expertise in Python (including asynchronous programming, packaging, and performance optimization) and the ability to deliver scalable, maintainable solutions beyond infrastructure configuration. Experience with Go is a plus.
• Strong CI/CD engineering experience for AI and agentic workloads: model and agent deployment, versioning, canary/blue-green strategies, evaluation gates, and rollback.
• Demonstrated experience implementing evaluation and guardrail frameworks for AI and agentic systems, including automated evaluations, drift detection, human-in-the-loop verification, and feedback loops in production environments.
• Demonstrated experience implementing security controls for cloud-native or production environments, including network policies, secrets management, vulnerability scanning, and access controls within regulated environments.

Responsibilities

• Architect end-to-end agentic resolution platform: 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 data contracts for durable fixes from upstream engineering teams.
• Define and maintain infrastructure as code (Terraform) integrated with cloud AI stacks, with secrets management and audit-ready posture.

Skills

Kubernetes

Python

Go

CI/CD

AI observability

Security

Education

Bachelor's degree in Computer Science or related

Tools

Terraform

AWS Bedrock/SageMaker

Azure AI Foundry

Vertex AI

LangChain

LangGraph

Job description

Lilly in Indianapolis, Indiana, seeks a senior platform engineer to own the agentic resolution platform end to end, including the cloud-native substrate and intelligent agents. You will write production code, design architecture, and set engineering standards to deflect routine operational work.

This senior IC role blends strategy with hands-on delivery, focusing on reliability, developer velocity, and scalable agentic intelligence across cloud-native platforms in regulated environments.