Senior AI Product Engineer (Full-Stack)

Salary

Core Qualifications

Preferred Qualifications

Key Responsibilities

• •Own the technical direction for an AI-assisted product area from early discovery through production operation
• •Build across the stack: Python services and APIs, data flows, user-facing interfaces and the infrastructure needed to run them
• •Design robust LLM and agent-based workflows, including prompts, evaluations, feedback loops, observability and safeguards
• •Translate editorial research and user feedback into technical options, trade-offs and testable plans
• •Identify the smallest useful experiments that can resolve important technical or product uncertainty
• •Create architectures that support rapid learning now without preventing the strongest ideas from becoming durable products
• •Develop reusable platform capabilities and integration patterns that can support multiple content workflows
• •Set pragmatic standards for reliability, security, maintainability, quality and cost—and help the team apply them
• •Use AI coding tools fluently while critically reviewing their output and remaining accountable for the software you ship
• •Anticipate dependencies, investigate difficult failures across components and keep production systems effective as usage grows
• •Raise the engineering bar through design discussions, code reviews, pairing and informal mentoring
• •Navigate technical trade-offs with both technical and non-technical stakeholders, including when priorities or perspectives differ
• •Travel to Groningen for one or two days approximately once every two months to work with colleagues there