Lead AI Solutions Engineer, AI Labs

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The Lead AI Solutions Engineer, AI Labs, is a foundational role in building NPR's first Generative AI (GAI)-focused product development team. Reporting to the VP of AI Labs, this engineer will be responsible for the technical development and implementation of generative AI solutions. The core mission is to engineer systems that leverage GAI to enhance the quality and actionability of our content metadata, thereby directly supporting the organization's goals of improving content personalization and increasing editorial efficiency. This role involves hands-on work in integrating AI products into core NPR systems, ensuring solutions are scalable, align with ethical guidelines, and are built upon industry best practices. This is a critical opportunity to shape NPR's technical AI adoption and build a new, innovative function.

• →Engineering & Implementation: Design, develop, and deploy scalable Generative AI (GAI) solutions, focusing on enhancing content metadata quality and actionability to meet organizational objectives.
• →Architecture & Technical Best Practices: Establish and champion technical best practices for Generative AI systems, including MLOps, RAG architectures, prompt engineering, and model evaluation, ensuring high-quality, maintainable code.
• →Cross-functional Development: Collaborate closely with Product Managers, data scientists, software and infrastructure engineers, and relevant subject matter experts to translate product requirements and roadmaps into robust, production-ready AI systems.
• →System Optimization & Performance: Implement data-driven methods, A/B testing, and performance monitoring to optimize the efficiency, scalability, and impact of AI models and pipelines.
• →Technical Communication: Clearly articulate technical architectures, development progress, and engineering challenges to product and non-technical stakeholders.
• →Responsible AI: Integrate ethical AI principles and compliance standards directly into the design and implementation of all AI products, in alignment with company policies.
• →Technology Scouting: Research and evaluate emerging AI technologies, frameworks, and industry trends to drive continuous technical innovation within the AI Labs.

• 8+ years of professional experience in software development, data science, or machine learning engineering, with a focus on building and deploying production systems.
• 2+ years of hands-on experience working with generative AI, machine learning, or data products.
• Expert proficiency in Python and experience creating functional prototypes to validate technical feasibility and user flows.
• Demonstrable understanding and experience building products that leverage Large Language Models, RAG architectures, prompting, function calling, retrieval, vector databases, embeddings, fine-tuning, and model evaluation.
• Familiarity with building and integrating MCP servers and agentic workflows.
• Background in creating QA systems for AI processes and development.
• Excellent communication skills and the ability to clearly articulate technical architectures and challenges to product and non-technical stakeholders.
• A collaborative and respectful approach to work and an ability to adapt quickly to change.
• A deep commitment to the mission of NPR and to the responsible implementation of Generative AI technologies.

• Experience designing and building highly scalable, production-grade AI/ML pipelines and services.
• Proficiency with cloud platforms, particularly AWS and Google Cloud Platform (GCP) and MLOps tools, particularly MLFlow and Vertex AI. 
• Experience with DevOps practices, including CI/CD and enterprise infrastructure-as-code.
• Experience working in media organizations and an understanding of media delivery systems.

• Hybrid Permitted: This is a hybrid permitted role. Some aspects of this role require duties better performed at an NPR facility. The employee will be required to be in the office at the Washington, D.C. location at least two days a week. The employee must also reside in an NPR-supported location (D.C., MD, or VA).

• This is a full-time, exempt position.

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