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# Senior Product Manager, Intelligence

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[Apply for this job](#job-application)[View company](https://jobicy.com/company/datagrail.md)Share24 Aug 2026Published44Listing views4Application actions23 Sep 2026Apply before  Opportunity details

## About this role.

AI SummaryDataGrail is seeking a Senior Product Manager to own strategy and delivery for its Intelligence Suite, including Live Data Map, Assessments, and Risk Management. The role focuses on complex enterprise privacy, risk, and data-intelligence products, with substantial integration of the Vera AI agent. This PM will lead customer discovery, roadmap prioritization, cross-functional execution, adoption strategy, and product metrics in partnership with engineering, design, ML, marketing, and customer success. It is a high-impact, remote US role reporting to the Chief Product Officer and requiring strong autonomy, communication, and enterprise SaaS product experience.

## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

5/5EasyHard

### Pace & Pressure

5/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

5/5IndependentCollaborative

AI insightThe role requires end-to-end ownership of several data-heavy, enterprise products while shaping an AI strategy in a sensitive privacy and compliance domain. Success depends on independently making difficult prioritization decisions, synthesizing customer and technical input, and delivering meaningful improvements quickly.

## Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate$197,500US market range$170k–$230k0$253k

AI insightThe disclosed US base compensation range is $180,000 to $215,000 USD yearly, with a midpoint of $197,500. This is competitive for a senior enterprise B2B SaaS Product Manager owning complex AI-enabled privacy and data-intelligence products; a representative US market base-salary range is approximately $170,000 to $230,000 annually, excluding equity and benefits.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Product strategy](https://jobicy.com/jobs?search_keywords=Product%20strategy.md)[Roadmap ownership](https://jobicy.com/jobs?search_keywords=Roadmap%20ownership.md)[Enterprise B2B SaaS](https://jobicy.com/jobs?search_keywords=Enterprise%20B2B%20SaaS.md)[Data privacy](https://jobicy.com/jobs?search_keywords=Data%20privacy.md)[Risk management](https://jobicy.com/jobs?search_keywords=Risk%20management.md)[Customer discovery](https://jobicy.com/jobs?search_keywords=Customer%20discovery.md)[AI product management](https://jobicy.com/jobs?search_keywords=AI%20product%20management.md)[Machine learning collaboration](https://jobicy.com/jobs?search_keywords=Machine%20learning%20collaboration.md)[Cross-functional leadership](https://jobicy.com/jobs?search_keywords=Cross-functional%20leadership.md)[Product analytics](https://jobicy.com/jobs?search_keywords=Product%20analytics.md)

Sample interview questionsHow would you prioritize improvements across Live Data Map, Assessments, and Risk Management when customers and internal teams have competing requests?I would first frame requests against shared product outcomes such as risk reduction, adoption, retention, revenue impact, and strategic differentiation. I would combine customer evidence with usage data, technical feasibility, and expected effort, then make tradeoffs explicit in a prioritized roadmap. I would communicate both what is prioritized and why lower-priority requests are deferred.

Describe how you would validate an AI-enabled feature before committing significant engineering resources.

I would begin with a clearly defined customer problem, target persona, and measurable hypothesis. I would use customer interviews, workflow mapping, lightweight prototypes, and AI-assisted demos to test whether the feature is understandable, trusted, and valuable. If evidence is positive, I would define an MVP with quality, safety, adoption, and business-success metrics before scaling investment.

What metrics would you use to measure success for a data privacy intelligence product?

I would track activation and adoption by persona, frequency of product engagement, time to discover or assess data risks, completion of recommended actions, and reduction in manual work. For business impact, I would evaluate retention, expansion signals, customer satisfaction, and the relationship between intelligence-suite usage and account health. Metrics should be segmented by customer maturity and use case to avoid misleading aggregate conclusions.

How do you conduct meaningful customer discovery with legal, privacy, and security stakeholders?

I focus on their real workflows, decision points, constraints, and consequences rather than collecting feature requests. I ask for recent examples, observe existing processes where possible, and distinguish symptoms from root problems. I synthesize findings into opportunity areas, validate them with additional customers, and share concise evidence with the product team.

How would you handle disagreement with engineering or leadership about a roadmap decision?

I would make the decision criteria transparent by presenting customer evidence, expected impact, delivery risk, alternatives, and the cost of delay. I would actively seek the technical perspective early, especially for data quality, security, and scalability concerns. When uncertainty remains, I would propose a time-boxed experiment or phased release that creates evidence while protecting the broader roadmap.

### The Opportunity:

Data privacy has become one of the most strategic challenges facing modern enterprises, sitting at the intersection of AI governance, data operations, and customer trust. As companies adopt AI at scale, they need new ways to understand where personal data lives, assess risk, and make confident decisions without slowing innovation.

DataGrail is the agentic data privacy platform built for the AI era. Our AI agent, Vera, helps the world’s leading brands discover, manage, and protect personal data across thousands of systems automatically, transforming work that was once manual and time-consuming into something teams can actually scale.

We’re looking for a Senior Product Manager to lead our Intelligence Suite, including Live Data Map, Assessments, and Risk Management. These products give customers the visibility they need to understand their data landscape, identify risk, and take action. They’re foundational to DataGrail’s platform today and central to where we’re investing over the next several years.

This is a high-impact role on a small, experienced product team where you’ll have broad ownership and the autonomy to move quickly. DataGrail is an AI-first organization, and our PMs use AI throughout the product development process—from exploring customer problems and validating ideas to building working prototypes that accelerate engineering execution. You’ll report directly to the Chief Product Officer and partner closely with engineering, design, and ML to shape both product strategy and execution. If you’re energized by talking to customers, rapidly testing ideas, and seeing your work make an immediate impact, you’ll thrive here.

### What You’ll Do:

* Own the full product strategy and roadmap for Live Data Map, Assessments, and Risk Management
* Make prioritization calls that balance customer needs, business goals, and technical feasibility
* Drive deep integration of Vera AI capabilities across the intelligence suite
* Run ongoing customer discovery with privacy, legal, and security stakeholders at mid-market and enterprise companies
* Lead cross-functional execution with engineering, design, and ML from problem definition through launch
* Partner with PMM and CS on positioning, enablement, and adoption
* Define success metrics and iterate based on what the data shows
* Build working prototypes using AI tools to make ideas tangible before handing off to engineering

### What You’ll Bring:

* 5+ years of product management experience in enterprise B2B SaaS
* Track record of owning complex, data-heavy products end-to-end
* Strong instincts for simplifying hard problems without losing depth
* Comfortable working directly with engineers and ML practitioners
* Experience doing real customer discovery — not just gathering requirements
* Clear communicator who can write a crisp brief, run a tight prioritization session, and present tradeoffs to leadership without hand-holding
* Fluency with AI tools and a default toward using them to move faster

Bonus Points

* Familiarity with privacy or compliance domains
* Experience shipping ML-powered or data intelligence products
* Background in platforms serving legal, compliance, or security personas

### What success looks like

### Within 90 Days You’ll:

* Develop deep familiarity with Live Data Map, Assessments, and Risk Management — the product, the customers, and the current roadmap. You’ll understand these products like the back of your hand, being an expert in how they function, and how customers use these products.
* Complete discovery conversations with key customers and internal stakeholders across CS, sales, and engineering
* Identify the highest-leverage near-term opportunities in the intelligence suite and present a prioritized point of view
* Ship multiple meaningful improvements to the product that directly influence DataGrail customer outcomes
* Take ownership of the intelligence roadmap and begin driving prioritization decisions with the team

### Within 180 Days You’ll:

* Own the intelligence roadmap end-to-end with minimal oversight
* Have a clear thesis on how Vera AI deepens the value of your products and a plan to execute it
* Be the go-to voice internally for your product area — in planning, in GTM conversations, and with customers
* Establish a regular cadence of customer engagement that informs your roadmap

### Within 365 Days You’ll:

* Have shipped multiple significant product bets across the intelligence suite
* Measurably grown engagement, adoption, or retention across your products
* Be a meaningful contributor to DataGrail’s overall product strategy and AI direction
* Set the bar for what great PM work looks like at DataGrail

Please note that the base compensation range below is a guideline and the final compensation will be based on factors such as qualifications, skill level, and competencies. Our compensation ranges apply to all US-based job postings regardless of state.

All full-time regular employees are eligible for equity, health, dental & vision insurance plans, remote-first working environment, 401k savings plan, parental leave, wellness benefits, flexible time off, paid holidays, and a work from home stipend. Benefits are subject to change.

Compensation Range

$180,000—$215,000 USD

### About Us:

DataGrail is the Agentic Data Privacy Platform. We help the world’s leading brands such as HubSpot, FanDuel, Dexcom, Major League Soccer, and Okta automate privacy and control risk with secure, human-governed AI that scales.

Powered by Vera, the complete privacy AI agent, and underpinned by an unrivaled 2,500+ integrations and no-compromise security architecture, DataGrail is built to solve complex privacy challenges that others can’t. DataGrail is rated 4.8/5 stars on G2 and is a two-time recognized privacy leader by IDC.

DataGrail provides equal opportunities for everyone that works for us and everyone that applies to join our team, without regard to sex or gender, gender identity, gender expression, age, race, religious creed, color, national origin, ancestry, pregnancy, physical or mental disability, medical condition, genetic information, marital status, sexual orientation, any service, past, present, or future, in the uniformed services of the United States (military or veteran status), or any other consideration protected by federal, state, or local law. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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