Bloomberg

Global financial data, news, analytics provider

Team Leader - Code Generation, Data AI

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeNew York, NY, USAIn-person

About the Job

Requirements

Significant experience in applied artificial intelligence, 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, application programming interfaces, data structures, evaluation design, and system behavior.
Strong understanding of generative artificial intelligence workflows and how evaluation data, annotation, grounding, structured representations, and quality measurement can improve model and product performance.
Experience evaluating generated code or structured outputs using metrics, error analysis, execution results, and other signals of correctness, reliability, and production readiness.
Strong analytical, communication, and coordination skills, with the ability to turn ambiguous client or system problems into structured, measurable improvement strategies across technical, product, and domain partners.

Responsibilities

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, focusing 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.

Desired Qualifications

Experience building or evaluating natural language to code, query generation, agentic systems, or other client-facing generative AI applications.
Hands-on experience with Python, SQL, application programming interfaces, structured data, schemas, data pipelines, or similar technical tooling.
Familiarity with BQL or other domain-specific query languages.
Experience designing evaluation frameworks, automated evaluation systems, benchmarking approaches, error taxonomies, or annotation strategies for generative AI.
Familiarity with execution-based evaluation, root-cause analysis, issue discovery, production monitoring, or closed-loop AI quality improvement workflows.
Experience in financial services or another complex, domain-rich environment, with a track record of mentoring technical contributors and raising technical capabilities across a team.

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 results, and other signals of correctness, reliability, and production readiness.
Strong analytical, communication, and coordination skills, with the ability to turn ambiguous client or system problems into structured, measurable improvement strategies across technical, product, and domain partners.

We'd Love to See:

Experience building or evaluating natural language to code, query generation, agentic systems, or other client-facing generative AI applications.
Hands-on experience with Python, SQL, APIs, structured data, schemas, data pipelines, or similar technical tooling.
Familiarity with BQL or other domain-specific query languages.
Experience designing evaluation frameworks, automated evaluation systems, benchmarking approaches, error taxonomies, or annotation strategies for generative AI.
Familiarity with execution-based evaluation, root-cause analysis, issue discovery, production monitoring, or closed-loop AI quality improvement workflows.
Experience in financial services or another complex, domain-rich environment, with a track record of mentoring technical contributors and raising technical capabilities across a team.

Salary Range = 135,000 - 230,000 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.

Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

About the Company

Bloomberg

Global financial data, news, analytics provider

Bloomberg provides financial data, news, and analysis to help professionals make informed decisions and operate more transparently and efficiently. Its products deliver trusted information and insights through technology platforms that connect global financial communities, enable collaboration, and support decision-making. The company differentiates itself by offering broad, reliable data and news across markets, strong customer focus, and a culture that emphasizes collaboration, broad perspective, and doing the right thing for clients, people, and communities. Bloomberg’s goal is to improve market transparency and efficiency by delivering accurate information and tools that empower customers to act confidently and ethically.

Company size: 10,001+
Company stage: Not listed
Total funding: Not listed
Headquarters: New York City, New York
Founded: 1981

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