Team Leader - Code Generation, Data AI

Location

New York

Business Area

Data

Ref #

10053334

Description & Requirements Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock - from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology - quickly and accurately. We apply problem-solving skills to identify workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.

Our Team The Bloomberg Data AI group brings modern AI technologies into Bloomberg’s Data organization while contributing deep financial domain expertise to the development of AI-powered products. We partner closely with partners to align AI innovation with Bloomberg’s strategic objectives, focusing on optimizing data workflows and elevating the quality, intelligence, and usability of the data that drives our products.

Our work amplifies the impact of the Data organization by delivering intelligent data solutions and domain-informed systems that improve the capabilities and competitiveness of Bloomberg’s offerings.

What’s the Role? As Bloomberg’s AI-powered code generation products continue to grow in scale and importance, we are seeking a Team Leader to provide technical and operational leadership across workstreams focused on improving the quality, reliability, and effectiveness of client-facing AI experiences. This is a hands-on leadership role focused on connecting work across a highly autonomous team, establishing shared technical and quality standards, and helping workstreams move from experimentation to scalable production.

You will act as a force multiplier for the team by providing technical direction, resolving ambiguity, identifying dependencies, and enabling workstream leads to execute independently while remaining aligned to a common strategy. A key part of the role will be advancing technical practices across the team, strengthening how we evaluate correctness and failure modes, and expanding the use of automation and tooling to improve client outcomes. Working closely with Product, Engineering, Data partners, and the CTO’s Office, you will help translate client needs, financial domain expertise, and model behavior into measurable improvements in Bloomberg’s code generation capabilities.

We’ll Trust You To

• Provide technical and operational leadership across client-facing code generation and agent workstreams, aligning leads on priorities, technical direction, quality standards, and delivery expectations.
• Establish shared technical and evaluation practices for natural language to code, structured generation, and agent workflows, with a focus on correctness, reliability, and client experience.
• Partner with Engineering, Product, AI teams, and domain experts to translate client and product needs into scalable generation, evaluation, annotation, and improvement strategies.
• Define and improve evaluation methodologies for generated code and structured outputs, including correctness, semantic fidelity, execution quality, robustness, and failure analysis.
• Drive improvements in client-facing AI outcomes by scaling the tooling, automation, data pipelines, annotation workflows, and evaluation frameworks used to identify and address model and system failures.
• Serve as a technical escalation point and force multiplier by resolving ambiguity, identifying cross-workstream dependencies, advancing technical practices, and contributing hands-on to high-priority problems.

You’ll Need To Have

• Significant experience in applied AI, machine learning, code generation, evaluation, data, software engineering, or a closely related technical field.
• Experience providing technical leadership across multiple projects or workstreams, including influencing peers and leading through expertise rather than formal authority.
• Strong technical fluency and the ability to engage credibly with Engineering and AI partners on prompts, schemas, APIs, data structures, evaluation design, and system behavior.
• Strong understanding of generative AI workflows and how evaluation data, annotation, grounding, structured representations, and quality measurement can be used to improve model and product performance.
• Experience evaluating generated code or structured outputs using metrics, error analysis, execution…