Staff, AI & Technology Enablement Manager

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

Requirements

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

Qualifications

Required:
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

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 (see more about our compensation and benefits at Intuit®: Careers | Benefits).

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