Senior AI Engineer

🕒 September 8

🌐 United Kingdom, Germany, +4 more countries – Remote

🇬🇧 United Kingdom – Remote 🇩🇪 Germany – Remote 🇮🇪 Ireland – Remote 🇳🇱 Netherlands – Remote 🇵🇹 Portugal – Remote 🇪🇸 Spain – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

🇬🇧 UK Skilled Worker Visa Sponsor

This company has sponsored UK Skilled Worker visas in the past.

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Typeform

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2012

📣 Marketing

💼 Consulting

🏥 Healthcare

Marketing • Consulting • Healthcare

Typeform is a versatile online form builder that enables businesses to create forms, surveys, and quizzes that are engaging and easy to use. With a focus on delivering a superior user experience, Typeform designs forms that break the mold by using branded designs, video content, and dynamic questioning that adapts based on previous answers. Ideal for B2B marketers, Typeform not only facilitates data collection but also offers AI analysis to derive insights from customer data, helping businesses make more informed decisions. Typeform integrates seamlessly with numerous apps, providing robust and dynamic solutions for marketing, research, human resources, and customer success teams.

📋 Description

• Design, build, and deploy generative AI capabilities across Typeform’s products • Develop applications using large language models, RAG, vector search, and agentic systems • Build services and APIs for integrating AI capabilities into customer experiences • Turn prototypes into reliable production systems with measurable performance and quality • Design and operate machine learning services and workflows using Python, Docker, Kubernetes, and AWS • Build batch and real-time processing pipelines using technologies such as Kafka and Airflow • Design vector-database solutions for retrieval, recommendations, personalisation, and semantic search • Manage experiments, model versions, registries, and deployments with MLflow • Build automated evaluation pipelines and benchmarks for generative AI quality • Evaluate retrieval strategies including chunking, embeddings, context selection, and reranking • Monitor production AI systems and improve quality, performance, reliability, scalability, and cost efficiency • Create safeguards protecting customer data and reducing unexpected behavior • Establish reusable AI engineering patterns and technical standards • Partner with Product, Engineering, Data Science, Data Engineering, and Analytics teams • Turn experiments and models into reliable production services • Contribute to technical planning and shape Typeform’s AI direction • Share technical knowledge and support other engineers

🎯 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 AWS SageMaker or AWS Bedrock • Experience with Kafka, vector databases, or 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 in technical decisions • Strong communication skills and experience collaborating with Product, Engineering, and Data teams