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.

Minimum Qualifications

• 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.

Preferred Qualifications

• 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.

Required Skills/Competencies

• 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.

Education Requirements

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

Work Location & Requirements

• 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.

Job Type

• This is a full-time, exempt position.

Compensation

Salary Range: The U.S.-based anticipated salary range for this opportunity is $180,000 - 206,000 plus benefits. The range displayed reflects the minimum and maximum salaries NPR expects to provide for new hires for the position across all US locations.

NPR Benefits: NPR provides comprehensive benefits for employees and dependents. Regular, full-time employees scheduled to work 30 hours or more per week are eligible to enroll in NPR’s benefits options. Benefits include access to health and wellness, paid time off, and financial well-being. Plan options include medical, dental, vision, life/ accidental death and dismemberment, long-term disability, short-term disability, and voluntary retirement savings to all eligible NPR employees.

Does this sound like you? If so, we want to hear from you.

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The range displayed reflects the minimum and maximum salaries NPR expects to provide for new hires for the position across all US locations.

NPR Pay Range

$180,000

—

$206,000 USD

NPR is an Equal Opportunity Employer. NPR is committed to being an inclusive workplace that welcomes diverse and unique perspectives, all working toward the same goal – to create a more informed public. Qualified applicants receive consideration for employment without regard to race, color, ethnicity, national origin, ancestry, age, religion, religious belief, sex (including pregnancy, childbirth and related medical conditions, lactation, and reproductive health decisions), sexual orientation, gender, gender identity or expression, transgender status, gender non-conforming status, intersex status, sexual stereotypes, nationality, citizenship status, personal appearance, marital status, family status, family responsibilities, military status, veteran status, mental and physical disability, medical condition, genetic information, genetic characteristics of yourself or a family member, political views and affiliation, unemployment status, protective order status, status as a victim of domestic violence, sexual assault, or stalking, or any other basis prohibited under applicable law.

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