Lead GenAI Engineer (LLM)

Being good neighbors – helping people, investing in our communities, and making the world a better place – is who we are at State Farm. It is at the core of how we operate and the reason for our success. Come join a #1 team and do some good! HYBRID: Qualified candidates must live or relocate within a 180-mile radius of a hub location listed below and should plan to spend time working from home and some time working in the office as part of our hybrid work environment. HUB LOCATIONS: Bloomington, IL; Dunwoody, GA; Richardson, TX; or Tempe, AZ  SPONSORSHIP:  Applicants for this position are required to be eligible to lawfully work in the U.S. immediately; employer will not sponsor applicants for U.S. work authorization (e.g. H-1B visa) for this opportunity Grow Your Skills, Grow Your Potential Responsibilities State Farm’s contact centers serve as the main connection to customers, agents, and associates, handling 10’s of millions of contacts annually. Our team is building the next generation of AI and GenAI systems that put insights, intelligent applications, and automated workflows into the hands of enterprise leaders. We work at the frontier of large language models, agentic architectures, and cloud-native AI — delivering solutions that are reliable, explainable, and that enhance human decision making. Join us if you want to see your code drive decisions at scale and help customers in their time of greatest need. In This Role, You Will: Design & Deploy AI/GenAI Solutions — Architect and implement LLM-powered applications, agentic workflows, & RAG pipelines using AWS Bedrock and AgentCore Build AI-Integrated APIs — Develop and maintain robust APIs (REST, FastAPI, etc.) serving as the backbone for AI applications, orchestration, and downstream consumers Engineer Data & Analytics Pipelines — Build pipelines that feed AI/ML systems with clean, governed, and well-structured data from enterprise sources Build on Amazon Bedrock AgentCore primitives — Runtime, Gateway (MCP), Memory, and Code Interpreter — to deliver streaming, stateful, tool-using agents in production. Champion Responsible AI — Apply prompt engineering best practices, implement guardrails, evaluate model outputs (Promptfoo, RAGAS), and ensure compliance with enterprise AI governance standards Drive Full Stack AI Applications — Build and maintain cloud-native web applications that surface AI capabilities to end users, including chat interfaces, dashboards, and automation tools Implement DevSecOps for AI — Integrate AI workloads into CI/CD pipelines, apply secure coding standards, and implement observability for model behavior and inference performance Enhance User Experience — Design intuitive AI-powered interfaces that are accessible, explainable, and trusted by end users Document & Share Knowledge — Author technical documentation, evaluation frameworks, and contribute to internal AI communities of practice Mentor & Lead — Provide technical guidance, code reviews, and foster a culture of responsible AI innovation Qualifications Preferred Skills Hands-on experience building LLM-powered applications, RAG pipelines, or agentic systems Strong foundation in software engineering: design, development, testing, and deployment of enterprise-grade applications Experience with cloud architecture (AWS preferred), Git version control, and performance optimization Experience with multi-agent orchestration patterns and tool-use frameworks (function calling, MCP) Proficiency in Python and/or TypeScript for API and AI integration development Familiarity with prompt engineering, model evaluation, and AI safety/guardrails Experience writing clear technical documentation, test cases, and evaluation frameworks Proficiency with AI-assisted development tools (GitHub Copilot) to accelerate delivery Strong communication skills with the ability to explain AI concepts to non-technical stakeholders Demonstrate initiative in learning emerging AI