Interested in this AI Product Manager role at Intuit?
Apply Now →Skills & Technologies
About This Role
Overview
------------
Come join the Virtual Expert Platform (VEP) team, where our mission is to be the AI\+HI (Human Intelligence) platform that unites the best of human expertise with AI to deliver transformational outcomes.
We are driving the flywheel of AI and HI: codifying human expertise to train AI, and building the infrastructure that allows us to leverage AI to continuously elevate HI expertise. We make these capabilities available across all Intuit products (TurboTax, QuickBooks, Mailchimp, Credit Karma). This is a rare opportunity to lead a paradigm shift in Fintech, solving the most critical and complex financial challenges for consumers and small businesses worldwide, and transforming Intuit from a software company into an AI\-driven expert platform that fuels prosperity.
We are seeking a visionary Principal Technical Product Manager to architect Intuit’s next\-generation Agentic AI Platform, supporting complex reasoning, autonomous task execution, and intelligent orchestration. You will be responsible for designing and delivering robust, scalable Agent Libraries and Execution Frameworks. This role delivers core common capabilities—making complex agentic behaviors, multi\-step planning, and orchestration easily consumable for product teams.
Responsibilities
- Define the Agentic Framework: Define, own, and articulate a compelling vision and roadmap for the core execution platform, ensuring it is flexible enough to support diverse use cases.
- Build Reusable Assets: Lead the development of reusable agent libraries and SDKs that standardize how agents are built, deployed, and managed, partnering deeply with engineers and architects to ensure developer velocity.
- Architect for Extensibility: Champion a "Platform First" architecture by defining requirements for extensible execution lifecycles. You will ensure the platform supports critical extension points for custom logging, validation, decision modification, and robust error handling.
- Drive Orchestration Logic: Drive product definition for advanced orchestration capabilities, including multi\-step planning execution, enabling agents to decompose complex problems into logical sequences.
- Ensure Observability \& Trust: Design and execute strategies for agent observability, ensuring we can trace execution paths, monitor plan validity, and maintain high performance and trust at scale.
- Influence \& Mentor: Practice boundaryless collaboration, building strong working relationships and influencing roadmaps across senior leaders. You will also mentor and raise the bar for other Product Managers on technical fluency and platform thinking.
Qualifications
- Experience: 8\+ years of product management experience.
- AI \& Platform Depth: Deep understanding and significant hands\-on experience defining strategy for and shipping products leveraging LLM\-based agentic systems, or workflow orchestration at scale.
- Technical Fluency: Strong technical intuition; comfortable engaging deeply with engineering on framework design, API contracts, state management, and the software lifecycle of AI agents.
- Strategic Translation: Proven ability to translate complex technical concepts (like execution loops and interception logic) into clear product requirements and strategic narratives.
- Customer Obsession: A staunch advocate for both end\-users and the internal developer customer, solving for their friction with urgency.
- Speed as a Habit: Ability to operate in a fast\-moving environment, make quick, data\-driven decisions with imperfect information, and execute fiercely to deliver outcomes.
- Curiosity: A high degree of curiosity, a learning mindset, and a bias towards experimentation to learn quickly.
- Education: Bachelor’s degree required with a focus in Computer Science, Engineering, Data Science, or a related quantitative/technical field preferred. An MBA or advanced technical degree is a plus.
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:
Bay Area California $ 236,000\- 319,000
Southern California $ 213,500\- 288,500
Salary Context
This $213K-$319K range is above the 75th percentile for AI Product Manager roles in our dataset (median: $174K across 475 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 26,159 AI roles we're tracking, AI Product Manager positions make up 2% of the market. At Intuit, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $204,600 based on 532 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($266K) sits 30% above the category median. Disclosed range: $213K to $319K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Intuit AI Hiring
Intuit has 43 open AI roles right now. They're hiring across AI Product Manager, Data Scientist, AI Software Engineer, AI/ML Engineer. Positions span Mountain View, CA, US, New York, NY, US, Sacramento, CA, US. Compensation range: $122K - $352K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.