AI Engineer

Want to shape how one of the world's leading publishers builds with AI?

Join Penguin Random House as our first AI Engineer, and help build the AI-powered products that are changing how we understand, publish and sell books.

Our Data Science and Analytics team builds data-driven tools that help us make smarter, ethical and commercially responsible decisions across our books. As our work has grown in scale and ambition, AI has transformed what we build and how quickly we can build it. We're now creating AI-powered applications that make teams faster and crack business problems that were out of reach only a few years ago.

We're also part of Penguin Random House's global community of AI and ML engineers, working with colleagues in the US and around the world to share tools, compare notes and shape how data science and AI are done across the company.

As our AI Engineer, you'll be at the heart of this work, bringing together strong software engineering, a solid grounding in machine learning and hands‑on generative AI experience. You'll design and build language‑model workflows for summarisation, extraction, classification and search, and add natural‑language interfaces and conversational search to the products our colleagues use every day. You'll also own the AI models we rely on.

That means testing, deploying and caring for them over time, so that we choose models on evidence and keep costs in check.

Beyond the products themselves, you'll lead the team's use of AI coding assistants, setting the standards, shared skills and workflows that let us move fast without cutting corners. You'll work hand in hand with our ML Engineers and ML Infrastructure Engineers: they build the models and the platform, and you build the AI products on top. You'll also be the go‑to person for prompt and agent development, teaming up with colleagues across Sales, Marketing and Editorial to turn their ideas into solutions that scale, using AI where it fits best and saying so when it doesn't.

If you'd rather build AI that's useful, reliable and responsible than AI that simply impresses in a demo, and you love helping the people around you level up, we'd love to hear from you.

• Design, build and improve language‑model‑based workflows for tasks such as classification, summarisation, extraction, generation and search, and develop the Python services, APIs and internal tools that integrate these into day‑to‑day business workflows
• Own model evaluation across projects: design and run the testing of new AI models and providers, maintain evaluation frameworks and datasets, and make evidence‑based recommendations that balance quality, speed, reliability and cost
• Own the AI model lifecycle: manage the deployment, configuration, ongoing maintenance, upgrade and retirement of the AI models in use by the team, working with ML Infrastructure Engineers on gateway, serving and observability
• Monitor AI usage and cost across our applications, identify edge cases and failure modes, and improve system behaviour and reliability
• Work with teams across Sales, Marketing, Editorial and the broader business to translate their needs into clear, scalable solutions, directing our effort and applying AI where it best fits – and advising when it does not
• Lead AI code assistance for the team: develop and maintain common standards, skill files, agent configurations and workflows; establish best practice for the use of AI tools; and ensure the team is upskilled with the latest developments
• Liaise with our US and global colleagues to share knowledge and tooling, and ensure we keep pace with them
• Support other teams with prompt development and agent development where this intersects with our remit, turning today’s…