AI Engineer (LLM)

State Farm•Dunwoody, GA

10h•Hybrid

About The Position

State Farm is a leader in building with modern, trending AI technology. The Power Platform team is hiring a software engineer to add to our growing enablement of AI technology. We are building a Future-Ready technology Platform!! Software engineers skilled in AI technologies and developer tooling including Model Context Protocol (MCP), agentic orchestration, A2A protocol, and large language model integration to mature platform capabilities in the organization will be competitive for this role. We work closely with our Microsoft engineering and product partners to enable the newest capabilities.

Requirements

3+ years of professional full stack development software engineering experience using Javascript/React and Python
Experience with the Model Context Protocol (MCP) or similar tool-use frameworks for LLMs
Experience working with or integrating AI/ML tools, APIs, or platforms (e.g., OpenAI API, Azure AI, AWS Bedrock, or similar)
Solid understanding of modern software development workflows including CI/CD, version control (Git), and code review practices
Hands-on experience building or customizing agentic AI workflows (e.g., multi-step autonomous coding agents, spec driven development, etc.)
Familiarity with IDE ecosystems and developer tooling (e.g., VS Code extensions, CLI tools)

Nice To Haves

Familiarity with Power Platform
Contributions to open-source projects related to AI, developer tooling, or code generation
Strong problem-solving skills and ability to work independently as well as collaboratively
Excellent written and verbal communication skills
Significant multi-tasking skills

Responsibilities

Design, build, and maintain AI-driven orchestration pipelines that coordinate LLMs, connectors, and enterprise data sources across the Power Platform ecosystem.
Develop agentic and autonomous workflows using emerging AI capabilities (Copilot Studio, agentic orchestration patterns, MCP, A2A protocol) to enable self-directed task execution and multi-stop reasoning.
Implement Model Context Protocol (capital MCP) integrations to unify model access to enterprise systems, ensuring secure, governed, and scalable interactions between AI agents and organizational data.
Engineer reusable AI components and abstractions (skills, actions, connectors) that accelerate adoption of AI across business areas and reduced duplication of effort.
Collaborate with Microsoft product and engineering teams to evaluate and adopt new AI platform features, providing feedback that shapes roadmap alignment for enterprise scenarios.
Build guardrails, patterns, and governance controls for AI agents, ensuring responsible use, audit trail, and compliance with enterprise security policy.
Optimize LLM-powered experiences by tuning prompts, grounding knowledge, retrieval pipelines, and context management patterns for reliability and performance at scale.
Develop telemetry, monitoring, and observability frameworks to track agent behavior, model performance, and orchestration health across distributed AI workloads.
Partner with product owners and business stakeholders to translate ambiguous AI opportunities into concrete technical solutions that deliver measurable business value.
Drive experimentation and rapid prototyping of new AI capabilities, validating feasibility and guiding enterprise adoption strategies.
Contribute to internal enablement and best practice documentation to uplift engineering teams building AI powered solutions on the power platform.
Contribute to Community uplift and support, creating a culture unique to our organization.