Senior AI Engineer

Salary: £65,000 - 100,000 per year

Requirements:

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

Responsibilities:

• Design, build, and deploy generative AI capabilities across our products.
• Develop applications using large language models, RAG, vector search, and agentic systems.
• Build services and APIs that enable product teams to integrate AI capabilities into customer experiences.
• Turn prototypes into reliable production systems with clear measures of performance and quality.
• Explore new ways for customers to collect, understand, and act on information using AI.
• Design and operate machine learning services and workflows using Python, Docker, Kubernetes, and AWS.
• Build reliable batch and real-time processing pipelines using technologies such as Kafka and Airflow.
• Design solutions using vector databases for retrieval, recommendations, personalisation, and semantic search.
• Use MLflow to manage experiments, model versions, registries, and deployments.
• Improve the reliability, performance, scalability, and cost efficiency of our AI systems.
• Build automated evaluation pipelines and benchmarks for generative AI applications, measuring factors such as accuracy, relevance, reliability, fairness, latency, and cost.
• Evaluate retrieval strategies, including chunking, embeddings, context selection, and reranking.
• Monitor AI systems in production, identify opportunities to improve quality and performance, and create safeguards that reduce unexpected behaviour and protect customer data.
• Establish reusable patterns and technical standards for building, evaluating, and releasing AI systems.
• Help teams make informed decisions about models, frameworks, infrastructure, performance, and cost.
• Apply strong engineering practices across testing, security, observability, version control, and deployment.
• Share technical knowledge and support the development of other engineers.
• Keep up with relevant AI research, tools, and engineering practices, applying what is useful to Typeform.
• Partner with Product, Engineering, Data Science, Data Engineering, and Analytics teams to connect AI investments with customer and business needs.
• Work with Data Scientists to turn experiments and models into reliable production services.
• Communicate technical concepts, risks, and trade-offs clearly to technical and nontechnical partners.
• Contribute to technical planning and help shape the direction of AI across Typeform.

Technologies:

• AI
• Airflow
• AWS
• OpenSearch
• Datadog
• Docker
• FastAPI
• HubSpot
• Support
• Kafka
• Kubernetes
• Machine Learning
• MLflow
• PyTorch
• Python
• RAG
• SQL
• Security
• Slack
• Snowflake
• Spark
• Terraform
• Zapier
• Cloud

More:

We are Typeform, a form builder that helps more than 150,000 businesses collect data through forms, surveys, and quizzes. Our products are designed to look striking and feel effortless to complete, drive 500 million responses each year, and integrate with tools including Slack, Zapier, and HubSpot. We are fully remote by design and can hire for this role in the UK, Ireland, Germany, Portugal, Spain, or the Netherlands. As a Senior AI Engineer, you will join our AI Engineering team, which builds the systems and capabilities behind our products using machine learning, large language models, RAG, and agentic systems. The team owns the journey from experimentation to production and works closely with Product Managers, Software Engineers, Data Scientists, Data Engineers, and Analytics teams. We value individual perspectives, teamwork, respect, transparency, and trust, and are committed to an inclusive workplace where everyone is welcome. We are an equal-opportunity employer and do not tolerate discrimination or harassment.

last updated 40 week of 2026