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About This Role
Location: New York, New York Team: Technology Product Job Requisition \#: R264999 Date posted: Jun. 30, 2026
Job description
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About this role
Role Summary
Technical Product Manager responsible for leading AI\-driven enterprise platform initiatives, with ownership across product strategy, execution, and go\-to\-market. Drives cross\-functional alignment across engineering, infrastructure, and business stakeholders to deliver scalable, enterprise\-grade solutions.
Key Responsibilities
1\. Product Strategy \& Roadmap Ownership
- Define and execute product strategy aligned to organizational objectives
- Translate complex, competing priorities into clear, actionable roadmaps
- Drive prioritization decisions across multiple teams and stakeholders
2\. AI \& Platform Innovation
- Lead development and adoption of AI\-powered solutions (e.g., enterprise chatbots, automation tools)
- Build and deploy internal tools leveraging modern AI frameworks and APIs
- Identify opportunities to scale automation and reduce manual operational effort
3\. Cross\-Functional Leadership
- Partner with engineering, infrastructure, operations, and vendors
- Drive alignment across large\-scale, distributed engineering teams (10\+ teams)
- Bridge technical and business domains by translating engineering insights into executive narratives
4\. Data\-Driven Decision Making
- Conduct user discovery and stakeholder interviews to identify friction points
- Leverage analytics and AI to synthesize large volumes of signals into actionable insights
- Build dashboards and reporting frameworks to support leadership decision\-making
5\. Drive adoption of alternative solutions across regulated environments
6\. Operational Excellence \& Process Design
- Design scalable processes, frameworks, and operating models (e.g., workflows, RACI)
- Improve engineering productivity and capacity allocation
- Ensure quality, reliability, and compliance in product delivery
Required Qualifications
- Experience in Technical Product Management within enterprise or SaaS environments
- Proven track record of managing complex, cross\-functional initiatives
- Strong understanding of AI/ML applications in enterprise platforms
- Ability to translate technical concepts into business impact narratives
- Experience working with distributed engineering teams and stakeholder groups
- Strong analytical and problem\-solving capabilities
Preferred Qualifications
- Experience with ServiceNow or enterprise workflow platforms
- Familiarity with cloud infrastructure and enterprise system integrations
- Hands\-on experience with tools such as Python, SQL, APIs, or prototyping tools
- Exposure to regulated environments (e.g., FIPS\-compliant systems)
- Background in data\-driven product discovery and experimentation
For New York, NY Only the salary range for this position is USD$162,500\.00 \- USD$215,000\.00 . Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits. BlackRock operates a pay\-for\-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.
Our benefits
To help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
Our hybrid work model
BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.
Guidance on AI use for candidates
At BlackRock, AI has long been part of how we work – enhancing decision\-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we’ve provided guidance( opens in new window) on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.
About BlackRock
At BlackRock, we are all connected by one mission: to help more and more people experience financial well\-being. Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.
This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.
To learn more about BlackRock, please visit Careers.BlackRock.com( opens in new window). We also encourage you to get to know us on LinkedIn( opens in new window), Instagram( opens in new window), YouTube( opens in new window), X( opens in new window), and TikTok( opens in new window).
BlackRock is proud to be an equal opportunity workplace. We are committed to equal employment opportunity to all applicants and existing employees, and we evaluate qualified applicants without regard to race, creed, color, national origin, sex (including pregnancy and gender identity/expression), sexual orientation, age, ancestry, physical or mental disability, marital status, political affiliation, religion, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law. View the EEOC’s Know Your Rights poster and its supplement( opens in new window) and the pay transparency statement( opens in new window).
BlackRock is committed to full inclusion of all qualified individuals and to providing reasonable accommodations or job modifications for individuals with disabilities. If reasonable accommodation/adjustments are needed throughout the employment process, please email [email protected]( opens in new window). All requests are treated in line with our privacy policy( opens in new window).( opens in new window)
BlackRock will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the requirements of the law, including any applicable fair chance law.
Job Requisition \#
R264999
Salary Context
This $162K-$215K range is above the median for AI Product Manager roles in our dataset (median: $188K across 140 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 3,708 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At BlackRock, 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 $216,175 based on 270 positions with disclosed compensation. This role's midpoint ($188K) sits 13% below the category median. Disclosed range: $162K to $215K.
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.
BlackRock AI Hiring
BlackRock has 5 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Based in New York, NY, US. Compensation range: $162K - $387K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
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 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).
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 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
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