Typeform·Germany (Remote) ; Ireland (Remote); Netherlands (Remote) ; Portugal (Remote) ; Spain (Remote) ; United Kingdom (Remote) ·3 дн назад
Senior Ai Engineer
🌍 УдалённоSeniorПолная занятость🌐 Глобал
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Наша компания
Typeform is a refreshingly different form builder. We help over 150,000 businesses collect the data they need with forms, surveys, and quizzes that people enjoy. Designed to look striking and feel effortless to fill out, Typeform drives 500 million responses every year—and integrates with essential tools like Slack, Zapier, and Hubspot. The AI Engineering team builds the systems and capabilities behind Typeform’s products. We use machine learning, large language models, RAG, and agentic systems to help customers collect, understand, and act on information in more conversational and personalised ways. The team owns the journey from experimentation through to production. This includes AI application development, evaluation, infrastructure, deployment, observability, reliability, and performance. 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.
Чем предстоит заниматься
As a Senior AI Engineer at Typeform, you will design, build, and operate the systems behind our AI products
Your work will span generative AI applications, enterprise RAG systems, agentic workflows, model evaluation, machine learning pipelines, and the infrastructure required to run them reliably at scale
This is a hands on engineering role with strong ownership. You will help turn ideas and prototypes into production systems used by our customers. You will also help define the technical standards for developing, evaluating, deploying, and monitoring AI across Typeform
Things you will do
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 that allow 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 pipelines for batch and real time processing using technologies such as Kafka and Airflow
Design solutions using vector databases to support 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 for generative AI applications
Develop benchmarks that measure accuracy, relevance, reliability, fairness, latency, and cost
Evaluate retrieval strategies, including chunking, embeddings, context selection, and reranking
Monitor AI systems in production and identify opportunities to improve their quality and performance
Create safeguards that reduce unexpected behaviour and protect customer data
Наши требования
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
A 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
The 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
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
Typeform drives hundreds of millions of interactions each year, enabling conversational, human-centered experiences across the globe. We move as one team, empowering our collective efforts by valuing each individual’s unique perspective. This fosters strong bonds grounded in respect, transparency, and trust. We champion our diverse customer base by anticipating their needs and addressing their challenges with priority. Committed to excellence, we hold high expectations for ourselves and each other, continuously striving to deliver exceptional results
We are proud to be an equal-opportunity employer. We celebrate diversity and stand firmly against discrimination and harassment of any kind—whether based on race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, or veteran status
Дополнительно
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
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 tradeoffs clearly to technical and nontechnical partners
Contribute to technical planning and help shape the direction of AI across Typeform