Staff, AI & Technology Enablement Manager

Staff, AI & Technology Enablement Manager

Join a newly formed team at Intuit building the operational infrastructure that powers Expert Excellence. As Staff, AI & Technology Enablement Manager you will own the technology and AI capability that makes the team faster, smarter, and more scalable. You will design and automate operational workflows, build and deploy AI agents that reduce manual overhead and increase delivery velocity, and serve as the AI subject matter expert across Expert Excellence partnering with content, curriculum, and delivery teams to embed AI into the way work gets done. This is a hands-on builder role for someone who has deployed AI in production environments, knows how to drive adoption without mandate, and is energized by defining what an AI-native operations function looks like. You will work closely with senior leadership on org-wide AI strategy and have the mandate and the platform partnership to make it real.

Responsibilities

• Audit workflows across Expert Excellence to identify automation opportunities and prioritize based on business impact
• Map the learning production workflow identifying where friction accumulates and where automation can eliminate it
• Design and implement workflow infrastructure routing logic, status visibility, and exception handling so progress is observable without manual coordination overhead
• Own the PMO platform evaluation and implementation leading the transition from fragmented tooling by Q3 FY27
• Design, deploy, and iterate AI agents that address the highest-value automation opportunities across Expert Excellence
• Build and run an org-wide AI enablement program partnering with content, curriculum, and delivery teams to embed AI into their workflows and enabling teams to work with greater speed and efficiency
• Serve as Expert Excellence's internal AI subject matter expert staying current on platform capabilities, governance guidance, and emerging agentic patterns
• Assess, rationalize, and manage the technology stack owning build vs. buy vs. configure decisions and vendor relationships

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

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. 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: $166,000-$195,700

The expected base pay range for this position is: San Diego $173,000 - $234,000