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Bloomberg's AI is transforming how investment professionals discover information, run analysis, automate workflows and collaborate across their organizations. ASKB has quickly become a primary conversational interface for Bloomberg Terminal users — letting users interact with Bloomberg's data, analytics, news and applications in natural language, powered by specialized AI agents and grounded in three principles: accuracy, transparency and trusted content.
As firms increasingly look to deploy AI at an enterprise level, Bloomberg is bringing enterprise\-grade administration, governance and collaboration to its AI capabilities — so firms can adopt AI across teams and departments while maintaining security, governance and trust. This is one of Bloomberg's most exciting product areas, combining AI, enterprise software and workflow transformation.
The role
We're seeking a Product Manager to own AI capacity for Bloomberg's enterprise AI offering — how Bloomberg measures, packages and prices the storage and compute (tokens) behind ASKB as AI workflows scale. Reporting to the Team Lead for Enterprise AI, you'll own the capacity model end\-to\-end: the desktop allowance, enterprise tiers, the pooled\-capacity model and priority in ASKB responses — together with the metering, monitoring and decision data behind every capacity and pricing decision.
You'll define how we measure and package capacity — turning it into a scalable product that grows with usage and gives firms clear, manageable control over what they consume.
Define the capacity model. Own capacity — storage and tokens — and how it's structured: the desktop allowance versus subscribed enterprise tiers and pooled capacity, and how priority works in ASKB responses. Decide how firms buy, share and manage capacity across their users.
Meter, monitor and forecast. Own how Bloomberg measures, monitors and alerts on consumption at user, workflow and firm level, and the accuracy of the monitoring and forecasting that capacity and pricing decisions depend on.
Power the inputs for commercials. Own the capacity product's inputs to pricing and packaging — cost per user, workflow category, token and schedule constraints — and, in partnership with the Enterprise AI Team Lead and Finance, shape how capacity is packaged and how firms subscribe to and manage additional pooled capacity, within the broader enterprise commercial model.
You'll work closely with ASKB engineering, Finance and enterprise product and data teams, translate capacity needs into detailed Product Requirement Documents, and partner with the central admin workstream so firm admins can see and manage what they consume.
We'll trust you to
- Own the capacity model for Bloomberg's enterprise AI — storage and tokens, the desktop allowance, enterprise tiers, the pooled\-capacity model, and how capacity priority works in ASKB responses.
- Define metering, monitoring and alerting on consumption at user, workflow and firm level, and own the accuracy of capacity monitoring and forecasting.
- Own the decision data behind capacity and tiered pricing — cost per user, workflow category, token and schedule constraints — and turn it into clear packaging and pricing recommendations.
- Shape the input data for capacity commercials in partnership with the Enterprise AI Team Lead and Finance — how capacity is packaged and priced and how firms subscribe to and manage additional pooled capacity — consistent with the broader enterprise commercial model.
- Translate capacity needs into detailed PRDs and requirements for ASKB engineering and metering teams.
- Surface capacity controls and usage visibility to firm admins, partnering with the central admin tooling workstream so firms can manage what they consume.
- Define capacity KPIs — utilisation versus allowance, overage and upsell, and subscription revenue from capacity tiers — and use telemetry to shape direction.
- Work directly with enterprise clients to understand how they consume and want to manage AI capacity, and validate the model against real firm behaviour.
You'll need to have
- Strong product management experience within enterprise software, SaaS or AI enterprise platforms, including leading initiatives from concept through launch.
- Experience with usage\-based, consumption or capacity\-based products — metering, tiering, quotas or pooled entitlement models.
- Hands\-on experience with AI / LLM\-based products or infrastructure, with an understanding of tokens, compute and storage as cost drivers.
- Strong analytical and quantitative skills — comfortable modelling cost, consumption and unit economics from telemetry.
- A solid understanding of enterprise software administration, governance and entitlements.
- Experience authoring Product Requirement Documents and managing cross\-functional roadmaps.
- The ability to partner with commercial and finance stakeholders on packaging and pricing while owning the underlying product.
- Outstanding written and verbal communication, with the ability to influence stakeholders across Product, Engineering, Finance and Sales.
We'd love to see
- Experience with the Bloomberg Terminal or Bloomberg Enterprise products.
- Experience pricing or metering AI / LLM usage and token\-based cost models.
- Familiarity with SaaS commercial models — usage\-based pricing, pooled entitlements, overage and tiering.
- Experience building metering, billing or capacity\-management systems.
- Financial\-modelling and unit\-economics fluency.
- Domain fluency in financial markets and how regulated institutions evaluate technology.
Salary Range \= 140,000 \- 295,000 USD Annual \+ Benefits \+ Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) \+match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
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Accommodations
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Bloomberg provides reasonable adjustment/accommodation to individuals with disabilities. Please tell us if you require a reasonable adjustment/accommodation to apply for a job. Examples of reasonable adjustment/accommodation include but are not limited to making a change to the application process or work procedures, providing documents in an alternate format or using specialized equipment. To request an adjustment/accommodation to apply for a job, please email AMER\[email protected] (Americas), EMEA\[email protected] (Europe, the Middle East and Africa), or APAC\[email protected] (Asia\-Pacific), based on the region you are submitting an application for. We may share your information with a third party provider of accommodations services who may use this information to reach out to you for the purposes of accommodating your application.
Equal Opportunity
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Bloomberg is an equal opportunity employer and prohibits discrimination in employment. It is Bloomberg’s policy to provide equal opportunity and access for all persons, and the Company is committed to attracting, retaining, developing, and promoting the most qualified individuals without regard to age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, self\-identified or perceived sex, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy, childbirth or related medical conditions, or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law (each, a “Protected Characteristic”). Bloomberg prohibits treating applicants or employees less favorably in connection with the terms and conditions of employment, in all phases of the employment process, because of one or more Protected Characteristics.
Salary Context
This $140K-$295K range is above the median for AI Product Manager roles in our dataset (median: $185K across 167 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 4,317 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At Bloomberg, 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 in Demand for This Role
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 $217,100 based on 471 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. Disclosed range: $140K to $295K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Bloomberg AI Hiring
Bloomberg has 6 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Based in New York, NY, US. Compensation range: $180K - $350K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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