About The Position

Penguin Random House publishes more of the books people love than anyone else in the world and the Data Science team helps those books find their readers: recommendation systems that surface the right book for the right person, forecasting models that guide print runs and marketing spend, and AI-powered tools that support our publishing teams. We're hiring a Senior AI Solutions Engineer to build the systems behind this next wave of AI work for improving operations: agentic applications, LLM-powered services, and the interfaces (e.g. MCP servers) that connect AI models and assistants to our internal data and tools. You'll work at the intersection of a world-class publishing business and the modern AI stack, and you'll own what you build all the way to production.

Requirements

  • 3+ years building and shipping production-quality software, including hands-on work with machine learning or AI 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.

Nice To Haves

  • 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
  • Demonstrated fluency with the current LLM stack: retrieval-augmented generation, embeddings, prompt engineering, agentic patterns, and rigorous evaluation of generative systems

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.

Benefits

  • Medical/Prescription drug insurance
  • Dental
  • Vision
  • Health Care/Dependent Care Flexible Spending Account
  • Health Savings Account
  • Pre-Tax and Roth 401(k)
  • Short and Long-Term Disability Insurance
  • Life/AD&D Insurance
  • Commuter Benefits
  • Student Loan Repayment Program
  • Educational Assistance
  • generous paid time off
  • annual profit award or bonus, subject to Company results
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