Artificial Intelligence Engineer

Only locals to Austin, TX or Chicago, IL, Urbandale, IA

Role Summary:

Support the AI Enablement program by building and maintaining the tools, content, and processes that accelerate AI adoption across the organization. This individual will partner with AI Enablement leads and embedded AI coaches to turn successful use cases into reusable skills, agents, templates, workflows, and knowledge assets that can be shared across teams. The role aligns with the AI Enablement vision of providing reusable AI capabilities, onboarding resources, and adoption support across department.

Key Responsibilities:

• Build and maintain the AI Skills, Agents, and Templates Hub.

• Develop reusable AI skills, agents, workflows, and starter templates.

• Create onboarding material, documentation, and best practices.

• Manage intake, prioritization, and tracking of AI enablement requests.

• Support AI coaches in packaging and scaling successful team solutions.

• Measure adoption, maintain asset quality, and coordinate releases.

Working Model

• Acts as the central builder and operator for shared AI enablement capabilities.

• AI coaches identify use cases, provide domain expertise, validate solutions, and drive adoption within their teams.

• AI Enablement leadership sets priorities and strategic direction. This complements the embedded coach model announced across DSG.

Success Measures:

• Increased adoption of AI tools and resources.

• Growth of reusable skills, agents, and templates.

• Faster onboarding and knowledge sharing.

• Reduced duplication of effort across teams.

• Improved discoverability and reuse of AI solutions.

Additional Required Skills:

Python expertise

Github

AWS is a plus

AI Frameworks (ex. Langchain)

MCPs

RAG and Vector Database

Harness Engineering

Nice to have:

Big Data (Databricks)

Multi agent system design/development