Manager, AI Engineering and Vendor Operations

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NPR's AI Labs team is looking for a Manager of AI Engineering and Vendor Operations. This person will serve on the AI Labs leadership team and help inform NPR's AI technical strategy. We are seeking a player-coach style who understands the complexities of building adaptive and conscientious AI coding teams, and can help us apply rigor and standards to our infrastructure decisions and rollouts. In this role, you will supervise the mid-level engineering staff, provide mentorship and support to NPR's larger engineering teams and own the evaluation and deployment of the team's AI tools and vendors. This role suits someone who can weigh build-versus-buy decisions honestly, explain technical trade-offs to non-technical colleagues, and hold both vendors and our own work to NPR's standards for privacy, security, and accuracy. This is a chance to shape a new team and have a tangible effect on how NPR uses AI responsibly in service of its mission, on a team built on respect, trust, and work-life balance.

• →People Leadership: Manage and mentor a team of entry and mid-level AI engineers, including hiring, onboarding, and supporting each person's professional growth.
• →Delivery: Lead technical planning, scoping, and sprint execution for AI Labs engineering work, such as NPR's AI-powered metadata service, in partnership with AI Labs leadership and editorial and business stakeholders.
• →Engineering Standards: Work with AI Labs leadership to develop AI coding frameworks, practices, and expectations for the team.
• →Code Quality and Architecture: Review designs and code, and contribute hands-on where it helps the team, keeping systems maintainable, secure, and consistent with NPR's technical standards.
• →Testing and Evaluation: Build and maintain automated testing and model evaluation practices, including regression tests and evaluation checks before release, aligned with quality bars set by the product team.
• →Production Support: Coordinate the team's response to production bugs and infrastructure incidents, and lead follow-up reviews to prevent repeat problems.
• →Vendor Evaluation: Lead technical evaluations of AI vendors, models, and tools, covering architecture, data handling, security, and cost, and recommend whether NPR should build, buy, or partner.
• →NPR-wide AI Tool Review: Participate in AI Labs' review of AI tools requested by teams across NPR, working with IT Security through the vendor risk and security intake processes. AI Labs assesses, and IT and the Office of General Counsel approve.
• →Vendor Relationships: Take over day-to-day management of selected AI vendors and tools, from onboarding and seat provisioning through renewal and offboarding. 
• →Responsible Scaling: Track vendor usage, spend, and renewal dates against budget, and ensure AI systems scale securely and cost-effectively while maintaining strong data privacy protections.

• 5+ years of experience building and shipping production AI or machine learning systems, with deep hands-on knowledge of large language models and the systems built around them.
• 2+ years of experience managing or mentoring engineers.
• Experience setting engineering practices for a team, such as code review, testing, or deployment standards.
• Experience working with technology vendors and managing software tools, including security and data privacy reviews.
• Experience building automated testing, including methods for evaluating the quality of AI model outputs.
• Hands-on experience building in a major cloud environment (Azure, AWS, or GCP).
• Experience setting up automated testing, including methods for evaluating the quality of AI model outputs.
• Experience working across technical and non-technical teams, including explaining technical and cost trade-offs to people without a technical background and working with product managers to gather requirements from stakeholders.

• Experience in a media organization, newsroom, or public service institution.
• Experience onboarding staff into a new or growing team.
• Experience working with procurement, legal, or vendor risk teams on technology reviews.

• Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.

• Hybrid Permitted: This is a hybrid permitted role. Some aspects of this role include duties that are better performed at an NPR facility. The employee will be required to be in the office, preferably at the Washington, DC location, at least 2 days a week. The employee must also reside in an NPR-supported location based on the number of onsite days they choose.

• Strong Python skills and working knowledge of retrieval-augmented generation (RAG) and semantic search.
• Proficiency in design and architecture of AI systems and systems of AI evaluation
• Proficiency in SQL and cloud data warehouses such as BigQuery or Snowflake.
• Familiarity with model evaluation methods, prompt engineering, and API integration, including NPR's approved model families such as Claude, Gemini, Gemma, and Llama.
• Ability to assess vendor security documentation, data processing terms, and seat-based and usage-based pricing.
• Commitment to data privacy, AI ethics, and identifying and reducing bias.

• This is a full-time, exempt position.

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