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About This Role
Strength in Trust
OneTrust's mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn't slow teams down—it should accelerate what's possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society.
The Challenge
You cannot govern what you cannot see. AI is entering the enterprise faster than any technology before it—often without a ticket: a team deploys a foundation model endpoint in an unmonitored cloud account, an engineer self-hosts an open-weight model, or a SaaS vendor quietly adds an AI feature to a widely used tool.
OneTrust is looking for a Staff Product Manager to own Detection—the discovery layer that finds AI models, LLM applications, agents, and AI-enabled features wherever they run, and turns that visibility into a governable inventory. Detection is the front door to AI governance: every downstream risk assessment, policy control, and compliance obligation depends on the completeness and accuracy of what you surface.
Your Mission
Strategy & Roadmap
- Own product strategy for the Detection area across multiple related products, balancing delivery across the full product line.
- Set the Shadow AI detection strategy: discover unsanctioned models, applications, and agents; attribute owners; risk-rank assets; and route them into governance and remediation workflows.
- Define and sequence the coverage roadmap across detection surfaces, weighing build vs. partner decisions, connector investment, and the risk retired by each incremental surface.
- Establish the detection taxonomy and definition of a "discovered AI asset," bringing models, hosted endpoints, fine-tunes, RAG pipelines, agents, and embedded vendor features into one coherent inventory.
- Own the quality bar with measurable targets for coverage, precision, recall, time-to-discovery, and false-positive rate; make tradeoffs explicit.
- Identify adjacent opportunities, including continuous monitoring, AI bill of materials, third-party and supply-chain AI risk, and usage telemetry.
Cross-Functional Leadership
- Lead geographically distributed engineering, design, data science, and detection research teams through ambiguous, discovery-heavy problems.
- Align with Product Marketing, Sales, and Partners on positioning and go-to-market in a category where buyers compare coverage claims.
- Partner with Security, IT, and Legal stakeholders—internally and at design-partner customers—to test detection signals against real enterprise adoption.
- Work with Ecosystem and Partnerships on cloud marketplaces and integrations with adjacent tools (CSPM, SSPM, CASB, IdP, EDR, and SaaS management) where telemetry can be shared rather than rebuilt.
Technical & Domain Depth
- Serve as the Detection subject matter expert while building knowledge of adjacent AI governance and privacy products.
- Bring deep understanding of AI deployment, including managed model services (Bedrock, Azure OpenAI, Vertex AI), commercial LLM APIs, self-hosted open-weight models and inference servers, fine-tuning and training pipelines, vector databases, RAG architectures, and agent frameworks.
- Understand detection mechanics well enough to make hard approach decisions across API and control-plane enumeration, log and network telemetry, OAuth and identity analysis, code and dependency scanning, endpoint and browser signals, and vendor questionnaires or attestations where technical discovery cannot reach.
- Translate requirements from the EU AI Act, NIST AI RMF, ISO/IEC 42001, and emerging state AI laws into concrete detection and inventory requirements.
Escalation & Communication
- Serve as the primary escalation point for the product line, de-escalating issues and communicating clearly from individual engineers to executives.
- Represent Detection strategy with customers, analysts, and prospects, and bring those insights back into the roadmap.
Mentorship
- Informally mentor Product Managers and Associate Product Managers, sharing strategic and domain expertise.
- Raise the broader product organization's bar for reasoning about AI systems, detection quality, and evidence-based prioritization.
You Are
A subject matter expert who handles significant complexity and exercises independent judgment. You set direction when the problem space is still forming, are sought out by Product Managers for strategic guidance, and thrive while juggling multiple priorities under aggressive timelines. You are intellectually honest about detection quality: you would rather ship narrower coverage you can defend than a number that fails a customer audit.
Your Experience Includes
- Bachelor's degree in Computer Science, Engineering, Business, or a related field.
- 8+ years of Product Management experience.
- Proven success managing a product through its full lifecycle, including end-of-life planning.
- Experience shipping discovery, inventory, or detection products in security, data discovery, asset management, CSPM/SSPM/CASB, observability, or a comparable domain where coverage and signal quality are the product.
- Working fluency with cloud platforms and AI services, as well as on-premises and self-hosted inference stacks; able to contribute effectively in architecture reviews.
- Experience with integration and connector-heavy products, including maintaining them as upstream APIs change.
- Experience contributing to technical debt and automation-backlog planning.
- Recent experience using Agile/Scrum methodology.
- Hands-on professional use of AI tools (e.g., Claude, ChatGPT, Notion AI, or similar) to accelerate research synthesis, PRD writing, or roadmap analysis, with genuine enthusiasm for applying AI to product work.
Bonus Points For
- Familiarity with AI governance frameworks and regulation, including the EU AI Act, NIST AI RMF, and ISO/IEC 42001.
- Background in enterprise security or IT tooling, or experience selling to CISO and Chief Data/AI Officer buyers.
- Experience with data-quality or ML-driven classification problems where precision and recall are negotiated with customers.
- Exposure to agentic systems, MCP, or AI supply-chain risk.
Where we Work
We are embracing an office-first culture, encouraging three days a week in office for most roles, with meaningful opportunities to collaborate and celebrate in person.
Each role may have specific requirements or flexibility depending on the scope of the position, so we encourage you to verify this with your recruiter during your first interview.
Benefits
As an employee at OneTrust, you will be part of the OneTeam. That means you'll receive support physically, mentally, and emotionally so that you can do your best work both in and out of the office. This includes comprehensive healthcare coverage, flexible PTO, equity RSUs, annual performance bonus opportunities, retirement account support, 14+ weeks of paid parental leave, career development opportunities, company-paid privacy certification exam fees, and much more. Specific benefits differ by country. For more information, talk to your recruiter or visit onetrust.com/careers.
Resources
Check out the following to learn more about OneTrust and its people:
- OneTrust Careers on YouTube
- @LifeatOneTrust on Instagram
Your Data
You have the right to have your personal data updated or removed. You also have the right to have a copy of the information OneTrust holds about you. Further details about these rights are available on the website in our Privacy Overview. You can change your mind at any time and have your personal data removed from our database. In order to do this you must contact us and let us know you wish to be removed. The request should be made on the Data Subject Request Form.
Recruitment fraud warning: OneTrust is aware of scams involving false offers of employment with our company. The fraudulent jobs, interviews and job offers use fake websites, email addresses, group chat and text messages. Be aware that we never ask candidates for personal information, IDs or bank information during the interview process. We do not interview prospective candidates via instant message or group chat, and do not require candidates to purchase products or services, or process payments on our behalf as a condition of any employment offer. Please note that any legitimate interview availability requests will come directly from a OneTrust recruiter with an "@onetrust.com" email address. You may also receive legitimate emails from "@us.greenhouse-mail.io". Recruiters will only reach out to candidates who have applied for a role through our ATS (Greenhouse) or prospects via LinkedIn InMail. Job offers will come from a recruiter and may have a "@docusign.net" email address. For more information or if you have been targeted please reach out to [email protected].
Our Commitment to You
When you join OneTrust you are stepping onto a launching pad — the countdown has begun. The destination? A career without boundaries working alongside a diverse and inclusive crew who is passionate about doing meaningful work. As a pioneer, your voice and expertise will help chart the direction of an entirely new category. Our commitment to putting people first starts with you. Your growth is part of the mission. Our goal is to give you the power to embark on the next phase of your uniquely, unique career.
OneTrust provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by local laws.
Salary Context
This $139K-$186K range is below the median for AI Product Manager roles in our dataset (median: $193K across 99 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 9,653 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At OneTrust, 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 $220,200 based on 862 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($163K) sits 26% below the category median. Disclosed range: $139K to $186K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
OneTrust AI Hiring
OneTrust has 3 open AI roles right now. They're hiring across AI Product Manager, AI Software Engineer, AI/ML Engineer. Positions span Atlanta, GA, US, Madrid, Community of Madrid, Spain. Compensation range: $186K - $247K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. 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: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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
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