Software Engineer, Project, AI Platforms

Rockwell Automation is hiring a Software Engineer for its Platforms Engineering team. The role builds and operates shared AI services, SDKs, APIs, evaluation systems, and agent tools that enable product teams to integrate AI capabilities into industrial software.

Responsibilities:

• Design and build platform services, SDKs, and APIs that product teams use to embed AI capabilities in FactoryTalk Design Studio, FTOptix, and Logix Designer
• Build and maintain MCP servers and tool interfaces that give agents governed access to product, build, and test systems
• Develop evaluation suites and regression gates that measure AI feature quality, safety, latency, and cost before release
• Own subsystem design through implementation, test, and production operation, including observability and performance budgets
• Work with product teams, architects, and security to apply OT/ICS constraints such as IP protection, binary signing, and data boundaries to every AI feature
• Prototype and evaluate new models and agent patterns, and turn the ones that work into supported platform capabilities
• Improve the team's own AI-assisted development loop and share what works across engineering teams

Requirements:

• Bachelor's Degree or Equivalent Years of Relevant Work Experience
• Degree in Computer Science, Software Engineering, Electrical Engineering, or a related field
• Typically requires a minimum of 8 years of experience in software product development environment
• experience building and shipping production software in Python, C#, or C++
• Experience designing services or APIs that other engineering teams build on
• Hands-on experience using AI coding tools and LLM APIs in your day-to-day work
• Experience with Azure, containers, and CI/CD pipelines
• Experience building and evaluating LLM applications: tool calling, retrieval, agent frameworks, MCP, and offline eval design for non-deterministic behavior
• Familiarity with industrial automation concepts such as PLC programming, OPC UA, or engineering design tools
• Experience applying secure development practices to features that embed LLMs and agents
• Clear written and verbal communication across engineering, product, and architecture teams