Technical Program Manager, Smart Manufacturing AI Pathfinding & Innovation; AIPI) Boise, Idaho

** Job Summary – Technical Program Manager, Smart Manufacturing AI Pathfinding & Innovation (AIPI)
** We are seeking a highly strategic and technically fluent Technical Program Manager (TPM) to join our Smart Manufacturing AI Pathfinding & Innovation (AIPI) team. In this role, you will sit at the absolute forefront of technological discovery, guiding initiatives from speculative research concepts into functional proofs-of-concept (PoCs). This team focuses explicitly on exploring unproven AI architectures, next-generation large language models (LLMs), speculative multimodal systems, and emerging agentic frameworks.

As an AIPI TPM, you will thrive in deep ambiguity. You aren't just tracking timelines; you are structuring the discovery process itself. You will bridge the gap between research, machine learning engineers, infrastructure teams, and executive leaders to systematically de-risk and validate the future of our AI technical roadmap.

This role requires a strong technical foundation and hands-on experience in managing complex AI/ML and data-driven projects. You will collaborate with cross-functional teams including data scientists, engineers, SMEs, and senior leadership to define functional objectives, translate them into actionable plans, and ensure seamless execution.
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* Job Responsibilities:

*** Drive the daily work and enable the long-term strategy of AIPI programs.
* Develop and document processes and methodologies to drive consistency across AIPI initiatives.
* Represent the AIPI function in cross-functional operations initiatives/working teams/meetings to further priorities, establish relationships and act as liaison between organizations.
* Develop, coordinate, and sustain top-level organizational objectives with regular read-outs to senior/executive stakeholders.
* Oversee all aspects of AI pathfinding projects, including resourcing and timeline.
* Identify and work to close any technical gap or barrier stalling project achievement.
* Design and maintain scalable project roadmaps aligned with strategic goals.
* Act as a central point of contact and single source of truth for AIPI programs.
* Advise leadership on technical feasibility, risk mitigation, and resource allocation to optimize outcomes.
* Partner to identify technical bottlenecks, evaluate trade-offs, and decide when to pivot, scale, or sunset experimental paths.
* Remove technical and operational barriers so research teams can move fast.
* Communicate high-level technical risks and breakthroughs clearly to non-technical executives.
* Establish quick learning loops, milestones, and metrics for unproven technologies.
** Track Objective and Program/Project Progress:
*** Partner closely with stakeholders and SMEs to develop meaningful, measurable objectives and actions
* Implement and oversee key metrics to ensure deliverables are achieved and have desired impact
* Provide clear data analysis to communicate project status, results and business impact
* Propose and develop processes and policies to drive consistency across the organization and eliminate work for senior leadership
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* Minimum Qualifications:

*** Computer Science, Engineering or other related technical degree
* 5+ years experience in complex program management and demonstrated success in global program execution
* Expertise in program management, project management, and vendor relationship management
* Extensive experience interacting with senior executives.
* Strong problem-solving skills and the ability to make data-driven decisions in a fast-paced, dynamic environment.
* Proven ability to manage complex technical programs, coordinate cross-functional teams, and drive projects to successful completion while balancing competing priorities and constraints.
* Ability to navigate ambiguity, and shape unstructured, exploratory ideas into defined experimental roadmaps.
* AI Literacy:
Solid foundational understanding of AI concepts, including deep learning, neural network architectures, transformers, training vs. inference life cycles, and modern data processing workflows.