Used Tools & Technologies
Machine Learning NLP LLMRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Communication @ 5
Product Management @ 6
AI @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Bloomberg's Data organization delivers fast, deep, and reliable information through scalable technology. The Data Artificial Intelligence group integrates modern AI technologies into Bloomberg’s Data org to improve data workflows, quality, intelligence, and usability. This role focuses on building shared AI platform capabilities that enable teams across Bloomberg to automate and modernize data workflows using AI.
Responsibilities
- Define and evolve the vision, roadmap, and operating model for shared AI platform capabilities that support workflow automation.
- Partner with AI engineers and infrastructure teams to develop reusable tooling, evaluation frameworks, orchestration capabilities, and operational infrastructure for building and deploying AI-powered workflows at scale.
- Work with domain experts, platform teams, and operational partners to identify common workflow patterns and translate business needs into scalable platform capabilities and services.
- Establish standards, interfaces, governance approaches, and guidelines to promote consistency, interoperability, and responsible adoption of AI-powered workflows.
- Drive alignment and execution across Data, Engineering, Technology, and AI teams; balance platform investments with evolving business priorities.
- Define approaches for measuring workflow quality, reliability, and production readiness to ensure AI-enabled systems meet Bloomberg’s standards for accuracy and trust.
- Identify technical, operational, and organizational risks across platform capabilities, integrations, and workflow implementations; coordinate mitigation strategies.
- Capture findings, operationalize reusable patterns, and contribute to broad adoption of shared AI infrastructure, platform services, and workflow automation capabilities.
Requirements
- 8+ years of product management or related experience leading technical platform or infrastructure initiatives end-to-end.
- Proven track record partnering with engineers, AI/ML practitioners, and business partners to deliver scalable technology capabilities and measurable outcomes.
- Experience driving platform-oriented products or shared infrastructure that support multiple teams, workflows, or business domains.
- Strong ability to translate operational or business challenges into scalable platform capabilities, tooling, and workflows.
- Exceptional communication and influencing skills, able to align diverse technical and non-technical partners around shared priorities and standards.
- Demonstrated ability to bring structure to ambiguity, prioritize effectively, and drive disciplined execution across multifunctional organizations.
- Systems thinking and organizational skills, with experience designing scalable processes, frameworks, or operating models.
- Comfortable operating in fast-moving environments where priorities, technologies, and organizational needs evolve over time.
Nice to Have
- Familiarity with AI/ML technologies such as large language models, natural language processing, evaluation frameworks, or workflow orchestration systems.
- Experience building internal platforms, developer tooling, or enterprise workflow automation capabilities.
- Experience working with large-scale data systems, operational workflows, or distributed platform environments.
- Understanding of AI governance, model evaluation, or production deployment considerations for AI-powered systems.
- Experience operating in highly matrixed organizations and scaling adoption of emerging technologies responsibly.
Compensation
- Salary Range: 140,000 - 295,000 USD Annual + Benefits + Bonus
Benefits
- Comprehensive benefits which 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) with match, life insurance, and various wellness programs. (Contingent workers/contractors and interns are not provided benefits directly.)