Qualifications Required:

7+ years in learning technology, operations, or EdTech with demonstrated ownership of end-to-end systems — not just features Hands-on experience building and deploying AI or automation systems in production — real users, real adoption cycles, real measurement, not prototype-only Direct production experience with large language model APIs — prompt engineering, knowledge base design, retrieval-augmented generation, structured output parsing, and trust model design Experience designing and managing agentic AI systems — multi-agent architectures, human-in-the-loop approval patterns, audit trail design, and failure mode thinking Demonstrated ability to drive workflow adoption without mandate — through peer proof, demonstrated usefulness, and social enablement infrastructure Experience enabling a non-technical team to use AI tools independently — building the social and instructional layer alongside the technical one Comfort operating in the gap between L&D, operations, and technical systems — able to translate between business stakeholders and technical partners, and willing to push back on both Measurable track record of reducing operational friction through workflow redesign, automation, or platform consolidation — with before-and-after evidence Strong cross-functional influence skills — experience bringing stakeholders across business functions into alignment on a shared problem before building a shared solution Prior experience in a high-growth, high-ambiguity organization — comfortable building structure around chaos rather than waiting for it to resolve Bachelor's degree required; advanced degree in learning design, instructional technology, information systems, or related field preferred

Preferred:

Lean, Six Sigma, or equivalent process improvement methodology applied in a learning, operations, or professional services context Experience designing measurement systems that connect workflow signals to behavior-level outcomes — not activity metrics or completion rates Familiarity with enterprise learning ecosystems — LMS/LXP platforms, HRIS integrations, xAPI/LRS patterns, and the data structures that connect them Footer Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:

Mountain View:

$188,000•221,600

San Diego:

$173,000•203,000

New York:

$180,000•212,000

Atlanta/Charlotte/Dallas:

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