Manager, AI Engineering and Vendor Operations
OVERVIEW
A thriving, mission-driven multimedia organization, NPR produces award-winning news, information, and music programming in partnership with hundreds of independent public radio stations across the nation. The NPR audience values information, creativity, curiosity, and social responsibility – and our employees do too. We are innovators and leaders in diverse fields, from journalism and digital media to IT and development. Every day, our employees and member stations touch the lives of millions worldwide.
Across our organization, we’re building a workplace where collaboration is essential, diverse voices are heard, and inclusion is the key to our success. We are committed to doing the right thing in our journalism and in every role at NPR. This means that integrity, adherence to our ethical standards, and compliance with legal obligations are fundamental responsibilities for every employee at NPR.
Intro to Position
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.
Responsibilities
- 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.
The above duties and responsibilities are not an exhaustive list of required responsibilities, duties and skills. Other duties may be assigned, and this job description can be modified at any time.