Staff AI Engineer - EU

As Staff AI Engineer, you will shape the technical direction of Research Flow and the AI systems behind Typeform’s products. You’ll own cross-team engineering challenges, define architecture, and deliver production-grade AI capabilities at scale. You’ll connect AI components into a cohesive, dependable user experience while guiding reliability, performance, and security. This role offers impact across product design, experimentation, and deployment in a fast-moving, collaborative environment.

• Define and drive technical direction for Research Flow and AI-enabled study design, adaptive conversations, and research synthesis
• Lead architectural decisions across AI-assisted workflows and integration of AI capabilities with data flows and services
• Own complex AI engineering initiatives from problem framing to production delivery
• Build reusable services and APIs to enable consistent AI capabilities for product teams
• Design and operate scalable AI foundations including ML services, pipelines, and infrastructure
• Establish evaluation strategies and release criteria for generative AI applications
• Improve retrieval quality (chunking, embeddings, reranking) and connect offline evaluation with production monitoring
• Mentor engineers, elevate engineering practices, and drive alignment across Product, Engineering, Data Science, and Data Engineering

• Significant experience building and operating production ML/AI systems with leadership beyond individual projects
• Strong Python and software engineering skills with ability to contribute production code
• Experience designing production services using FastAPI
• Practical experience with generative AI, LLMs, RAG, tools or agentic systems
• Understanding of enterprise RAG architectures, retrieval, embeddings, and evaluation/monitoring
• Experience with PyTorch, LangChain, LangGraph, or similar
• Cloud proficiency with AWS, Docker, Kubernetes, Terraform; CI/CD practices
• Familiarity with AWS SageMaker or AWS Bedrock
• Experience with event-driven processing, vector databases, Kafka, and ML lifecycle tools (MLflow)
• Observability and production issue diagnosis using Datadog or OpenSearch
• Ability to influence technical decisions across teams and mentor others

• Collaborative mindset
• Strong technical judgment
• Clear communication with technical and non-technical partners
• Python
• FastAPI
• PyTorch