Interested in this AI/ML Engineer role at OneTrust?
Apply Now →Skills & Technologies
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
OneTrust is looking for a Vice President, Product Management to lead and scale our AI Governance business. This is not a caretaker role. It is a builder role for a product leader who knows how to create, scale, and operationalize category\-defining enterprise software.
AI Governance is one of the fastest\-emerging categories in enterprise software. The first Gartner Magic Quadrant for AI Governance was published this year, and OneTrust is positioned as a top vendor.
We are looking for a forward\-thinking domain builder and a platform\-focused executive. This person will guide the business. They should have good judgment to set direction and the credibility to lead in their field. They must help teams build, define priorities, and speed up execution. This leader will not operate as a high\-level delegator focused only on presentations and process. They will shape the strategy, strengthen the product foundation, and help teams solve hard problems — including prototyping directly with modern AI development and design tools to demonstrate product vision.
The Four Lenses We Are Hiring For
The right candidate threads the needle across four dimensions:
- Builder — Hands\-on prototyping and demonstrating product direction by building — not pontificating through slideware. When a team is stuck, you can open the tools and show them what great looks like.
- Domain expert — Depth in at least one core lens of AI Governance — risk \& compliance, security, identity \& access, data governance, or AI cost governance — with the range to connect that depth to the full landscape.
- Platform thinker — You design solutions as part of a broader platform, not isolated point products. You have built inside true platform businesses and think in systems: the solution is the spearhead, but the platform is the wood behind the arrow.
- Category builder — You have taken new categories from zero to $100M–$200M\+ — ideally more than once — and know how to use analysts, customers, and market proof points to scale an organization.
Your Mission
- Define and own the end\-to\-end product vision, strategy, and execution path for OneTrust's AI Governance solution
- Act as the first lens for the domain, bringing both breadth across AI Governance and depth in at least one core area that materially shapes product and market strategy
- Drive platform\-level thinking across the product, ensuring AI Governance capabilities are designed to scale within the broader OneTrust platform and partner ecosystem
- Partner closely with the SVP of AI Strategy, platform and engineering leaders, and executive team to double\-down \& accelerate the growth of AI Governance
- Translate fast\-moving market dynamics, customer AI\-stack decisions, competitive pressure, and commercial opportunity into differentiated product deliverables
- Work directly with Product Marketing, Sales, Sales Engineering, Partnerships, Customer Success, and Finance to align roadmap, pricing, packaging, and go\-to\-market execution
- Build and lead a high\-performing product organization with clear accountability, high standards, urgency, and customer obsession
- Lead customer listening mechanisms including Customer Advisory Board and voice\-of\-customer programs to ensure the roadmap reflects real market signal
- Serve as a credible external voice for OneTrust in AI Governance with customers, analysts, and strategic partners
- Own prioritization, resource allocation, and portfolio tradeoffs across the AI Governance offering
Who You Are
You are a product executive who builds, not just manages. You have helped take enterprise software products from early traction to material scale and know what it takes to create sustained growth in a fast\-moving market. You are equally comfortable setting multi\-year strategy, guiding executives through major business decisions, and working with teams on difficult product and platform problems.
You combine strategic range with practical depth, and you have the credibility to lead in a complex enterprise environment where trust, governance, and platform scale matter.
You have likely worked in or alongside category\-leading platform businesses and understand how to build products that operate as part of a broader platform, not as isolated point solutions. You have seen what great looks like in scaled enterprise software and can bring that standard to OneTrust.
Your Experience Includes
- Bachelor's degree in Computer Science, Engineering, Business, or a related field; MBA or advanced degree preferred
- 16\+ years of experience in enterprise software product management, including significant senior leadership experience
- A proven track record of helping scale a product or product line from early stage to a scaled business
- Broad understanding of the AI Governance landscape and the ability to connect domain depth to platform and business strategy
- Strong record of building products and organizations, including scaling platforms and internal culture
- 10\+ years of experience leading product managers, product leaders, and people managers, with a track record of building high\-performing and accountable teams
- Strong commercial instincts, including experience shaping product strategy based on market opportunity, customer economics, and revenue levers
- Experience fostering cross\-functional alignment with Sales, Marketing, Partnerships, Customer Success, and Finance
- Demonstrated ability to influence at the executive and C\-suite level internally and externally
- Strong judgment in prioritization, investment allocation, and platform tradeoff decisions
- Exceptional communication skills with the ability to articulate vision, create alignment, and represent the business credibly in the market
- Comfort operating in ambiguity and building structure, clarity, and momentum where they do not yet exist
Location
San Francisco, CA is the primary location preference. For exceptional candidates, other major hubs (Seattle, Denver, Atlanta, New York) will be considered.
### 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 $255K-$382K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At OneTrust, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. This role's midpoint ($318K) sits 46% above the category median. Disclosed range: $255K to $382K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
OneTrust AI Hiring
OneTrust has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in San Francisco, CA, US. Compensation range: $382K - $382K.
Location Context
AI roles in San Francisco pay a median of $277,088 across 810 tracked positions. That's 27% above the national median.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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.