Product Manager — AI Enterprise Capacity Management New York, NY Posted today

Product Manager — AI Enterprise Capacity Management

Location

New York

Business Area

Product

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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.

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.

• 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 ASBK 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.