Technical Program Manager – AI Foundations
Listed on 2026-01-13
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IT/Tech
AI Engineer, Data Science Manager, Machine Learning/ ML Engineer, Data Analyst
Staff Technical Program Manager – AI Foundations
Join to apply for the Staff Technical Program Manager – AI Foundations role at Intuit
OverviewCome join Intuit’s AI Foundations (AIF) organization as a Staff Technical Program Manager in our Mountain View office. AIF team empowers the democratization of AI across Intuit by building scalable, intuitive platforms, tools, and best practices that enable teams to confidently apply the right AI technologies to solve business problems. In this role, you will operate as a Program-level TPM, leading some of Intuit’s most complex and high-impact AI platform initiatives.
You will partner closely with engineering, product, architecture, Responsible AI, and business leaders to drive execution across GenOS, AI/ML life cycles, agentic systems, observability, and platform adoption. This is a highly ambiguous, fast-moving environment. We’re looking for someone who is comfortable operating in complex, evolving AI ecosystems, can bring structure to ambiguity, and can scale execution as the AI Foundations portfolio continues to expand.
Intuit has embraced a hybrid working model and this role requires 3 days in office per week.
What You’ll Do
- Own delivery of critical AI Foundations programs spanning AI/ML platforms, GenOS capabilities, agentic ecosystems, observability, Responsible AI, and platform adoption.
- Lead cross-functional execution across 20–30+ engineering, product, infrastructure, data, and governance teams distributed globally.
- Drive end-to-end AI platform initiatives, covering the full lifecycle.
- AI/ML and GenAI SDLC & MDLC
- Model experimentation, evaluation, and observability
- Agentic systems and orchestration
- Deployment, governance, and adoption at scale
- Partner with engineering and architecture leaders to translate AI strategy into executable roadmaps, milestones, and success metrics.
- Establish execution rigor: dependency management, risk identification, trade-off decisions, and proactive mitigation in highly ambiguous environments.
- Support AI platform adoption and maturity, ensuring teams can move from experimentation to production safely and efficiently.
- Drive alignment across AI standards and Responsible AI, helping embed governance, compliance, and quality into paved roads rather than manual processes.
- Provide executive-level visibility through clear, concise updates that synthesize technical complexity into business-relevant insights.
- Influence without authority, building trust and alignment across senior stakeholders in Engineering, Product, Security, Legal, and Data.
What We’re Looking For
Required Experience- 8+ years of Technical Program Management experience, leading large-scale, cross-org platform or infrastructure initiatives.
- Strong experience with AI/ML or GenAI platforms, including understanding of AI/ML life cycles (experimentation → evaluation → deployment → iteration)
- Model training, inference, and observability concepts
- Platform enablement for developers (paved roads, tooling, standards)
- Experience operating in highly complex, ambiguous environments with rapidly evolving technology and priorities.
- Proven ability to scale execution across multiple concurrent programs with interdependencies.
- Strong technical depth across cloud, platform, and infrastructure systems (e.g., AWS, distributed systems, APIs, CI/CD).
- Demonstrated success influencing senior engineering and product leaders without direct authority.
- Experience with AI/ML platforms, GenAI systems, or agentic architectures.
- Familiarity with concepts such as model orchestration, RAG, evaluation frameworks, observability, and Responsible AI.
- Experience driving platform adoption and capabilities across multiple teams, not just delivering platform features.
- Background working on foundational platforms used by many product teams.
- Ability to reason about cost, scale, and efficiency in AI/ML systems (e.g., model usage, infrastructure trade-offs).
- You bring structure to ambiguity and clarity to complex AI initiatives.
- You operate at the portfolio level, not just individual programs.
- You balance technical depth with business impact, knowing when to go…
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