AI Workforce Development Engineer

Micron TechnologyBoise, ID

About The Position

The AI Workforce Development Engineer is the technical builder behind SMAI's upskilling mission. You design and build the hands-on learning that turns AI strategy into capability: working labs, reference end-to-end (E2E) workflows, reusable templates and accelerators, and technical curriculum for emerging roles. You go deep on AI productivity tools and generative-AI platforms, codify Best Known Methods (BKMs) into teachable artifacts, and personally lead master classes and technical seminars. You partner closely with the Workforce Development Specialist, who runs the programs, partnerships, and communications that bring your content to the organization. This role is for an engineer who finds deep satisfaction in helping others build—scaling individual expertise into systems that lift entire teams.

Requirements

  • Bachelor's degree in Computer Science, Data Science, Engineering, or a related STEM field, or equivalent experience in practice.
  • 3+ years in a software engineering, machine-learning, data science, solutions/forward-deployed engineering, or technical consulting role.
  • Strong programming proficiency, particularly in Python (experience with JavaScript/TypeScript a plus).
  • Hands-on experience building with generative AI—LLMs, prompt engineering, retrieval-augmented generation (RAG), and/or agentic workflows—and common AI/ML frameworks.
  • Demonstrated ability to design and build end-to-end solutions or workflows, not just isolated components.
  • Proven ability to explain complex technical topics clearly and to teach, mentor, or enable other engineers.

Nice To Haves

  • Experience creating technical curriculum, workshops, labs, or developer enablement content at scale.
  • Familiarity with MLOps / LLMOps, cloud AI platforms, APIs, and integration patterns.
  • Experience building reusable templates, accelerators, or internal developer tooling.
  • Exposure to manufacturing, engineering, or industrial data and use cases.
  • Track record of driving measurable technical adoption inside an engineering organization.

Responsibilities

  • Build hands-on training content—labs, code samples, and exercises—for AI productivity tools, and capture Best Known Methods (BKMs) as reusable, teachable technical artifacts.
  • Design and develop reference end-to-end (E2E) AI workflows that demonstrate new ways of working, and turn them into templates and patterns teams can learn from and reuse.
  • Develop the technical curriculum and capstone projects that upskill team members into emerging roles such as AI Product Owner and E2E AI Full-Stack Developer.
  • Evaluate, configure, and integrate AI tooling and platforms with our skills/learning environment, including sandboxes and hands-on lab infrastructure.
  • Serve as a technical point of contact with our technology partners—evaluating new capabilities, validating features, and translating partner technology into practical SMAI enablement.
  • Co-develop technical content and projects with our select group of strategic university collaborators.
  • Design and personally deliver Generative AI master classes, including live coding, demos, and deep-dive technical sessions.
  • Build prototypes, demos, and proofs-of-concept that drive innovation sharing across SMAI and make new techniques tangible.
  • Lead and deliver data science technical seminars with rigorous, hands-on content.
  • Provide technical mentoring to TLP participants and help define the technical bar for advancement.
  • Build the templates, guardrails, accelerators, and starter kits that enable citizen developers across the enterprise to safely build with AI.
  • Create reusable enablement tooling and reference solutions that scale SMAI's expertise beyond the core team.

Benefits

  • Choice of medical, dental and vision plans
  • Benefit programs that help protect your income if you are unable to work due to illness or injury
  • Paid family leave
  • Robust paid time-off program
  • Paid holidays
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