Sr. Accelerator Design & Development Manager; AI Skilling
Listed on 2026-01-10
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IT/Tech
AI Engineer
Location: California
Sr. Accelerator Design & Development Manager (AI Skilling)
3 days ago Be among the first 25 applicants
AboutAt InStride, people are our purpose. We believe that investing in people is the most powerful way to drive success—for individuals and organizations alike. As a public benefit corporation, we partner with leading employers to unlock opportunities for their employees, providing access to top-tier education programs that align with their employees’ career goals and the company’s business goals. Our mission goes beyond skill‑building;
we're here to empower our partners’ employees to advance their careers, elevate their expertise, and achieve meaningful personal and professional growth. No matter the team you’re on, our dedication to the success of our partners and their employees is what drives us. If you're passionate about making a difference and driving educational and professional advancement, InStride is the place for you.
To get a better feel for our culture, watch more here. Candidates must be located in one of the following states to be considered eligible for employment: AZ, CA, CO, CT, FL, GA, IL, IN, KS, LA, MD, MA, MI, MO, NV, NH, NJ, NY, PA, OH, OR, TX, VA, WA, WI.
At InStride, we’re redefining how employers develop talent through applied, university‑quality learning that drives measurable business impact. Our Capability Accelerators are cohort‑based, role‑aligned programs, co‑developed with leading universities and employers, designed to build the skills that matter most for performance, productivity, and mobility demand accelerates for practical, responsible AI capability across the workforce, we’re hiring an Sr. Accelerator Design and Development Manager, AI Skilling to help lead this next chapter.
This role will focus on designing and scaling AI Capability Accelerators that enable non‑technical leaders and professionals to effectively apply AI in their day‑to‑day work, while partnering productively with technical teams and managing AI‑related risk. Reporting to the Director of Enterprise Learning, you will lead the end‑to‑end design and development of AI‑focused Accelerators, translating employer business priorities into clear capability models, role‑specific behaviors, and structured program blueprints.
You’ll work closely with academic partners, faculty, and industry experts to bring these programs to life, embedding applied use cases, deliberate practice, and AI‑enabled feedback mechanisms that drive real behavior change on the job. Beyond individual programs, this role plays a critical part in evolving InStride’s AI Accelerator model. You’ll help codify repeatable design frameworks, templates, and quality standards for AI skilling, ensuring our offerings remain rigorous, scalable, and differentiated as the market rapidly evolves.
This includes shaping how we integrate emerging AI tools and agents into learning experiences, while maintaining a strong focus on responsible use and business relevance. This is a hybrid strategic and hands‑on role. You’ll design flagship AI skilling programs for employers today, while building the systems and intellectual property that enable InStride to scale AI capability development across industries tomorrow.
we’d love to see you show off
- End‑to‑end AI program delivery:
Direct experience designing, launching, and delivering applied AI or advanced capability programs, with ownership from concept through live delivery and iteration. - Applied AI learning expertise:
Hands‑on experience using AI, simulations, and practice‑based learning to build real capability for non‑technical leaders and professionals. - Employer‑facing program leadership:
Proven ability to partner with senior L&D leaders and business stakeholders to translate priorities into delivered, high‑impact programs. - Scalable learning system design:
Ability to codify what works into repeatable models, templates, and playbooks that enable quality and scale. - Builder mentality:
Energized by shipping real programs, learning from what lands, and continuously improving the model in ambiguous, fast‑evolving environments.
- You’v…
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