Lead AI Platform Infrastructure Architect

Responsibilities

• As our AI Platform Architect, you will develop platforms that make it simple for teams across Rockwell to use AI.
• You will deliver working AI tools using infrastructure as code and create platforms that accelerate how quickly we can adopt and benefit from AI.
• This is a hands‑on role. You will write code, build pipelines, deploy infrastructure, and own what you ship.
• You will also partner with engineering, data, and security teams to make sure what you build fits into how we work.
• Build AI Platforms:
  You will deliver platforms that support the full AI lifecycle, from data ingestion and model training to deployment and monitoring.
• You will create reusable services and templates so teams can go from idea to production with less effort.
• You will ensure platforms are reliable, scalable, and straightforward to use.
• Deliver Infrastructure as Code:
  You will develop all platform components using infrastructure as code.
• You will create repeatable deployment patterns and automated pipelines.
• You will lead the automation that provisions, updates, and scales platform environments.
• Enable AI Adoption:
  You will build practical tools and services that reduce the barriers to using AI across the enterprise.
• You will create standardized paths for teams to build, test, and deploy AI solutions.
• You will focus on making the platform easy to adopt so teams spend their time on outcomes, not on setup.
• Integrate and Operate:
  You will connect data pipelines, model services, APIs, and monitoring into a cohesive platform.
• You will support both real‑time and batch AI workloads.
• You will ensure high availability, performance, cost efficiency, and security across all platform components.

• Bachelor's degree or equivalent years of relevant experience.
• Legal authorization to work in the U.S. We will not sponsor individuals for employment visas, now or in the future, for this job opening.
• Ability to travel domestically or internationally up to 10%.
• Typically requires 12+ years of experience in infrastructure architecture, platform engineering, or cloud engineering roles.
• Degree in Computer Science, Engineering, or a related technical field.
• Background in cloud infrastructure (Azure, AWS, or GCP) and hybrid enterprise environments.
• Hands‑on experience designing platforms using containers, Kubernetes, and infrastructure‑as‑code.
• Familiarity with AI/ML platform requirements, including GPU acceleration, high‑performance storage, and network throughput.
• Experience integrating security, identity, and compliance controls into shared platforms.
• Experience designing enterprise‑ready platforms that balance innovation, risk, and operational scalability.

• infrastructure as code
• AI tools development
• data ingestion
• model training
• deployment
• monitoring
• containers
• Kubernetes
• cloud infrastructure
• GPU acceleration

• collaboration
• leadership
• problem‑solving
• communication
• organizational skills
• adaptability
• innovation
• scalability focus
• customer‑oriented
• teamwork