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Typeform is a form builder used by over 150,000 businesses to collect data through forms, surveys, and quizzes. The company processes 500 million responses annually and integrates with tools like Slack, Zapier, and HubSpot.
The AI Engineering team builds systems and capabilities powering Typeform's AI-driven products. The team uses machine learning, large language models, RAG (retrieval-augmented generation), and agentic systems to help customers collect, understand, and act on information in conversational and personalized ways. The team owns the full journey from experimentation through production, including AI application development, evaluation, infrastructure, deployment, observability, reliability, and performance.
As a Senior AI Engineer, you will design, build, and operate systems behind Typeform's AI products. Your work spans generative AI applications, enterprise RAG systems, agentic workflows, model evaluation, machine learning pipelines, and the infrastructure to run them reliably at scale. This is a hands-on engineering role with strong ownership—you'll turn ideas and prototypes into production systems used by customers and help define technical standards for developing, evaluating, deploying, and monitoring AI across the company.
Key responsibilities include: designing and deploying generative AI capabilities; developing applications using LLMs, RAG, vector search, and agentic systems; building services and APIs for product teams to integrate AI; turning prototypes into reliable production systems with clear performance measures; designing and operating ML services using Python, Docker, Kubernetes, and AWS; building reliable pipelines for batch and real-time processing with Kafka and Airflow; designing vector database solutions for retrieval, recommendations, and semantic search; building automated evaluation pipelines for generative AI; developing benchmarks for accuracy, relevance, reliability, fairness, latency, and cost; monitoring production AI systems and identifying improvements; establishing reusable patterns and technical standards; helping teams make informed decisions about models, frameworks, and infrastructure; applying strong engineering practices across testing, security, observability, and deployment; and collaborating with Product, Engineering, Data Science, Data Engineering, and Analytics teams.
You will work closely with Product Managers, Software Engineers, Data Scientists, Data Engineers, and Analytics teams to turn promising AI ideas into secure, scalable, and dependable customer experiences.
