Senior AI Solutions Engineer, Data Science, Penguin Random House (Open to Remote)

Penguin Random House is a publishing company whose Data Science team develops recommendation systems, forecasting models, and AI-powered tools. The Senior AI Solutions Engineer will build, deploy, and operate LLM-powered applications, MCP servers, and AI integrations for internal data and operational systems, while evaluating emerging AI technologies and developing the team’s engineering capabilities.

Responsibilities:

• Design, build, and operate LLM-powered applications and services (e.g. agentic workflows, retrieval/RAG systems, classification pipelines) over our catalog, sales, and operational data
• Stand up and maintain MCP servers and tool integrations that connect AI models and assistants to our internal data and systems safely and reliably
• Own services end-to-end: architecture, implementation, deployment, evaluation, and monitoring in our AWS/Databricks environment
• Evaluate emerging AI tooling and patterns (agent frameworks, MCP, evaluation harnesses, new model capabilities), run structured pilots, and lead adoption of what works
• Raise the team's AI engineering capability: run working sessions and internal demos, pair program with scientists, and build internal tools to help accelerate AI usage across the team

Requirements:

• 3+ years building and shipping production-quality software, including hands-on work with machine learning or AI systems
• Demonstrated fluency with the current LLM stack: retrieval-augmented generation, embeddings, prompt engineering, agentic patterns, and rigorous evaluation of generative systems
• Strong Python engineering skills with experience in version control, testing, and CI
• Self-motivated, with strong communication skills and a demonstrated ability to teach and level up teammates
• Experience standing up MCP servers or comparable tool-integration layers for AI assistants
• Experience with cloud ML platforms (AWS, Databricks), model APIs (Bedrock, Anthropic, OpenAI), and vector databases
• Advanced degree (MS/PhD) in computer science, machine learning, or a related quantitative field
• Experience applying AI/ML to commercial problems such as demand forecasting, pricing, sales and marketing optimization, recommendation, or search
• Background in media, publishing, or other content-rich domains