GE Aerospace
AI & Automation Lead - Product Development
Evendale · Full-time · Posted Oct 28, 2026
- Experience
- Minimum of 3 years.
- Education
- Bachelor's degree in engineering, computer science or similar from an accredited university or college.
- Visa sponsorship
- Must obtain and maintain US Government Security Clearance, for which U.S. citizenship is a prerequisite. Employment also requires U.S. Person status for access to export-controlled information: U.S. lawful permanent resident, U.S. citizen, or granted asylee or refugee status. Must be legally authorized to work in the United States.
About the job
Leads the redesign of engineering processes and delivers AI and automation solutions integrated into product-development toolchains and classified environments.
What you'll do
- Map and redefine engineering workflows, prioritize AI and automation opportunities, and develop capability roadmaps.
- Integrate, guide development and deployment of, and continuously improve AI and automation tools across engineering platforms.
- Partner with engineering and support teams to validate solutions, drive adoption, and establish sustainable support.
What they ask for
- Bachelor's degree in engineering, computer science or similar from an accredited university or college.
- Minimum of 3 years of experience in engineering, manufacturing, digital technologies or other technical field.
- Experience with digital transformation and / or AI-native process redefinition, preferably with a focus on product development or manufacturing.
- Must obtain and maintain US Government Security Clearance; U.S. citizenship is a prerequisite.
Nice to have
- Working knowledge of AI/ML and generative AI tools and frameworks, data integration, databases, APIs, and web services.
- Proficiency in scripting and programming, modern development practices, cloud environments, and engineering tools such as Teamcenter, NX, Cameo, and Ansys.
Tools
Teamcenter, NX, Cameo, Ansys, PyTorch, scikit-learn, Python, AWS
AI focus
Evaluates and applies generative AI, agents, and ML models to engineering use cases; integrates AI into engineering workflows and toolchains and guides build-versus-buy-versus-leverage decisions.
Model-written summary · the original posting is authoritative