Senior AI Engineer

Join Typeform as a Senior AI Engineer and be a key player in building and evolving the AI capabilities behind Research Flow and other AI products. You will work closely with various teams to turn AI ideas into secure, scalable, and dependable customer experiences. Your responsibilities will include designing, building, and deploying generative AI capabilities, developing applications using large language models, and improving the reliability and performance of AI systems. This is a hands-on engineering role with strong ownership and direct influence on the quality and performance of the systems you build.

- Design, build, and deploy generative AI capabilities across Typeform’s products, with a key contribution to Research Flow. - Develop applications using large language models, RAG, vector search, and agentic systems, and turn prototypes into reliable production systems. - Establish reusable patterns and technical standards for building, evaluating, and releasing AI systems, and help teams make informed decisions about models, frameworks, infrastructure, performance, and cost.

- The ability to balance quality, speed, reliability, scalability, and cost when making technical decisions - Experience using services such as AWS SageMaker or AWS Bedrock - Experience building production services using Python frameworks such as FastAPI - At least four years of experience building and deploying machine learning or AI systems in production - Experience managing machine learning workflows using MLflow - Experience with AWS, Docker, Kubernetes, Terraform, and continuous integration and deployment practices - Experience with frameworks such as PyTorch, LangChain, LangGraph, or similar technologies - Strong communication skills and experience collaborating with Product, Engineering, and Data teams - Experience with Kafka, vector databases, or other technologies used for real time and high dimensional data processing - Experience monitoring production systems with tools such as Datadog or OpenSearch - Practical experience developing generative AI applications using large language models, RAG, tool use, or agentic systems - A strong understanding of enterprise RAG systems, including chunking, embeddings, retrieval, reranking, evaluation, and monitoring - Experience creating automated evaluations for generative AI applications - Strong Python and software engineering skills - Experience working in a B2B SaaS product company - Experience with orchestration tools such as Airflow or Argo Workflows - Familiarity with SQL, Spark, Snowflake, or other data processing technologies - Experience building systems that combine structured data, unstructured data, and generative AI - Experience with AI security, privacy, responsible AI, prompt injection protection, or data leakage prevention - Experience improving the latency and cost of AI systems operating at scale