This listing does not state pay. Across 88 open principal product manager listings that state pay, the middle half runs $208,500 to $245,500 and the median is $227,500.

Listed pay is what employers advertise, not what people are paid.

Principal Product Manager salaries by state · Check your own pay

How AI is used in this kind of work

Among marketing managers, AI is already used for a large share of the tasks. Measured exposure for marketing managers: 32% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

Check how this applies to your own job

Intuit has filed one layoff notice in the last twelve months, covering 162 workers, most recently May 2026. These are public filings with state labor departments, and an open role can sit alongside them. See the filings

Skills this job asks for

Say which you have and which you want to build. We use it to match you to jobs like this one.

Onboarding

About the job

Every risk decision is only as good as the data behind it. When a feature silently degrades, decisions drift and losses surface weeks later. When onboarding a new signal takes weeks of engineering work, fraud rings outrun the defense. The data layer is where risk platforms are won or lost.

We're hiring a Principal Product Manager to own the data and signals foundation of our risk platform: the single governed layer through which every rule, model, and AI agent consumes data. You'll build the contracted catalog of features, scores, and vendor attributes (with owners, freshness guarantees, and drift monitoring at the boundary), the decision-time data record that powers backtesting and model training, and the third-party data strategy that keeps our signals best in class.

Your customers are internal: risk analysts who need to self-serve data for new policies, data scientists who need full data parity between models and rules, engineers who need one contract instead of hundreds of point-to-point fetches, and operations teams who need the full picture behind a decision. You'll be measured on how fast and how safely all of them can move.

Responsibilities

Own the data boundary: define and deliver the governed data layer every risk decision passes through, with a versioned catalog, contracted freshness, and drift monitoring that catches degraded inputs in minutes instead of days. You own the results and the plans to get there.

Make data self-serve: take new-signal onboarding from an engineering project to an analyst workflow, so the person with the fraud-domain knowledge can wire data into a policy without a ticket.

Build the decision record: ensure every decision is logged with the data and versions that produced it, creating the joined history that backtesting, model retraining, and case investigation all consume.

Own the vendor portfolio: continuously evaluate third-party identity, device, and behavioral data partners; decide what to buy, what to build, and what to retire, balancing coverage, accuracy, and cost.

Set the contracts upstream: establish ownership and service agreements with the internal platforms that compute and serve our features, so changes reach risk decisions announced, not silently.

Own the metrics: instrument time-to-detect degraded data, time-to-onboard a new signal, data reuse across policies, and analyst self-serve rates; report progress and trade-offs to leaders across risk and platform teams.

Align and deliver: build strong relationships across engineering, data science, risk policy, and partner platform organizations; ruthlessly prioritize; set delivery timelines.

Qualifications

8+ years in Product Management, including sustained ownership of complex, technical, multi-team platform initiatives with accountability for measurable business outcomes.

Risk experience is required: you've worked in fraud, credit, identity, or financial risk and understand how data quality drives loss and false-positive outcomes.

Proven track record as a data platform PM: you've owned a feature store, data catalog, data contracts, or governed data layer serving production decision systems.

Experience with data vendors: evaluating, integrating, and operationalizing third-party data for decisioning, and managing the coverage-accuracy-cost trade-off.

Deep partnership with data science and ML/AI teams: you understand features, training/serving parity, and what models need from a data layer.

Strong technical fluency: streaming and batch data infrastructure, APIs, SLOs, observability, and real-time decisioning.

Quantitative rigor: comfortable setting numeric targets for freshness, latency, coverage, and reuse, and proving impact against them.

Exceptional communication: you translate data architecture trade-offs into clear narratives for executives and win alignment across organizations you don't control.

Bachelor's degree required; Master's degree or MBA preferred.

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 $243,000 - $328,500 New York $240,000- $325,000