Manager, AI Engineering and Vendor Operations

NPR•Washington, DC

2d•$180,000 - $206,000•Hybrid

About The Position

NPR's AI Labs team is seeking a Manager of AI Engineering and Vendor Operations to serve on the AI Labs leadership team and help shape NPR's AI technical strategy. This player-coach role supervises and mentors AI engineers, supports engineering teams across NPR, and leads evaluation and deployment of AI tools and vendors. The manager will help establish rigorous engineering practices and infrastructure standards, make build-versus-buy recommendations, communicate technical trade-offs to non-technical colleagues, and ensure vendors and systems meet NPR's standards for privacy, security, and accuracy. The position includes leadership of technical planning and delivery for AI Labs engineering work, including NPR's AI-powered metadata service; development of AI coding practices; architecture and code review; automated testing and model evaluation; production support; and vendor assessment and management. The role also participates in NPR-wide AI tool review alongside IT Security and supports responsible, secure, and cost-effective scaling of AI systems. This is a full-time, exempt position. It is hybrid permitted, with at least two days per week in an NPR office, preferably in Washington, DC. Employees must reside in an NPR-supported location based on their chosen number of onsite days. The anticipated U.S. salary range is $180,000–$206,000, plus benefits.

Requirements

At least 5 years of experience building and shipping production AI or machine-learning systems, with deep hands-on knowledge of large language models and related systems.
At least 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 working across technical and non-technical teams, explaining technical and cost trade-offs to non-technical colleagues, and working with product managers to gather stakeholder requirements.
Strong Python skills and working knowledge of retrieval-augmented generation (RAG) and semantic search.
Proficiency in AI system design and architecture and systems for 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 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 and AI ethics, including identifying and reducing bias.
Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.

Nice To Haves

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.

Responsibilities

Manage and mentor entry- and mid-level AI engineers, including hiring, onboarding, and supporting their professional growth.
Lead technical planning, scoping, and sprint execution for AI Labs engineering projects in partnership with AI Labs leadership and editorial and business stakeholders.
Work with AI Labs leadership to develop AI coding frameworks, practices, and team expectations.
Review designs and code, and contribute hands-on as appropriate, to keep systems maintainable, secure, and aligned with NPR's technical standards.
Build and maintain automated testing and model evaluation practices, including regression tests and pre-release evaluation checks aligned with product quality standards.
Coordinate responses to production bugs and infrastructure incidents and lead follow-up reviews to prevent recurring problems.
Evaluate AI vendors, models, and tools for architecture, data handling, security, and cost, and recommend whether NPR should build, buy, or partner.
Participate in AI Labs' review of AI tools requested by teams across NPR, working with IT Security through vendor-risk and security intake processes.
Manage selected AI vendor and tool relationships, including onboarding, seat provisioning, renewals, and offboarding.
Track vendor usage, spending, and renewal dates against budget, and ensure AI systems scale securely and cost-effectively while protecting data privacy.