Technical Product Manager - Content Platform

Bloomberg; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

Bloomberg is seeking a Product Manager for their Content Platform team in New York. The role involves defining how content is accessed and consumed across Bloomberg systems, including APIs and data feeds. Candidates should have a minimum of 5 years in product management, experience with data platforms, and strong API design skills. The position emphasizes collaboration with engineering and product teams to improve content delivery, ensuring efficiency and scalability across systems, especially in AI-driven projects.

Qualifications

• Minimum 5+ years of product management or related experience required.
• Experience managing APIs and distributed systems is essential.
• Strong understanding of API design and versioning is necessary.

Responsibilities

• Define projection layers derived from canonical content.
• Design and manage APIs, data feeds, and streaming interfaces.
• Partner with product and engineering teams to understand needs.
• Establish standards for latency, availability, and scalability.
• Monitor adoption and prioritize improvements for platform interfaces.

Skills

Product management

API design

Data platforms

Technical communication

Distributed systems

Job description

The Content Platform team owns the end-to-end platform and strategic direction for Bloomberg’s unstructured content across core domains including News, Research, Media, and other content types. The team is responsible for the canonical content model and the ingestion, storage, projection, and distribution capabilities that make content reliable, reusable, and consumable across downstream systems—particularly AI-driven use cases. Working in close partnership with Engineering, Data and other Product teams, the group ensures content is discoverable, indexable, and usable at scale across both the Bloomberg Terminal and Bloomberg's Enterprise lines of business. In addition, the team is accountable for platform-wide metrics, measurements, and statistics, providing transparent, quantifiable insight across every stage of the content lifecycle. Its mandate is to set the strategy, standards, and roadmap for unstructured content as a shared Bloomberg platform—ensuring consistency, scalability, and long-term leverage as content and consumption models evolve.

What's the role?

We are seeking a Product Manager to lead Delivery & Consumption for the Content Platform. In this role, you will define how canonical content is exposed and consumed across Bloomberg systems, including the Terminal, Enterprise products, search, and AI use cases.

You will own the projection layer and the distribution interfaces that make content accessible to downstream consumers. Working closely with engineering, AI, and product teams, you will ensure content is delivered in forms that meet latency, scalability, and reproducibility requirements while maintaining a consistent canonical model.

We’ll trust you to:

• Define and manage projection layers derived from canonical content, including low-latency views for real-time applications, historical snapshots for model training, and datasets for analytical workloads
• Design and own APIs, data feeds, and streaming interfaces used to distribute content, including interface contracts, versioning, and deprecation strategies
• Partner with product, AI, and engineering teams to understand consumption needs and ensure the platform supports production use cases without duplicated pipelines
• Establish and drive standards for latency, availability, and scalability across delivery mechanisms
• Monitor adoption and usage of platform interfaces, identify gaps, and prioritize improvements to increase reuse and consistency across Bloomberg systems

You’ll need to have:

• A minimum of 5+ years of product management or related experience
• Experience building or managing data platforms, APIs, or distributed systems used by multiple consumers
• Strong understanding of API design, versioning, and backward compatibility
• Technical fluency and the ability to work closely with engineering teams on architecture and system trade-offs
• Experience working across teams and communicating effectively with both technical and non-technical stakeholders

We’d love to see:

• Experience supporting AI or analytics workflows, including training data and low‑latency inference use cases
• Familiarity with streaming and batch processing architectures and data delivery patterns
• Experience working on internal platforms or shared infrastructure
• A pragmatic approach to balancing standardization with flexibility in a multi-consumer environment