Senior Ai Engineer

Senior Ai Engineer Overview

Typeform is a unique and innovative form builder that helps over 150,000 businesses gather essential data through engaging forms, surveys, and quizzes. Designed to be visually appealing and effortless to complete, Typeform handles over 500 million responses annually and integrates seamlessly with popular tools like Slack, Zapier, and Hubspot. The company operates fully remotely, and this particular role is open to candidates based in the United Kingdom, Ireland, Germany, Portugal, Spain, or The Netherlands.

About the AI Engineering Team

The AI Engineering team at Typeform is responsible for developing the systems and capabilities that power the company’s AI products, including Research Flowâ??a platform that combines quantitative research with qualitative insights. The team leverages machine learning, large language models, retrieval-augmented generation (RAG), and agentic systems to enable customers to collect, understand, and act on information in a conversational and personalized manner. From experimentation to deployment, the team manages AI application development, evaluation, infrastructure, deployment, observability, reliability, and performance. Collaboration with Product Managers, Software Engineers, Data Scientists, Data Engineers, and Analytics teams is essential to turn innovative AI ideas into secure, scalable, and dependable customer solutions.

Role Overview

As a Senior AI Engineer at Typeform, you will play a key role in developing and enhancing the AI capabilities behind Research Flow and other AI-driven products. Your work will enable customers to better understand responses and accelerate decision-making processes. Your responsibilities will include working on generative AI applications, enterprise RAG systems, agentic workflows, model evaluation, machine learning pipelines, and infrastructure to ensure these systems operate reliably at scale. This is a hands-on engineering position with significant ownership, where you will transform prototypes into production-ready systems that influence product quality and performance. You will also help define technical standards for AI development, evaluation, deployment, and monitoring across the organization.

Key Responsibilities

• Design, develop, and deploy AI features and products, focusing on Research Flow enhancements.
• Build applications utilizing large language models, RAG, vector search, and agentic systems for conversational and personalized experiences.
• Create APIs and services for integrating AI capabilities into various product components.
• Convert prototypes into reliable, scalable production systems with clear performance metrics.
• Explore innovative AI methods to improve data collection, understanding, and actionability for customers.
• Design and operate scalable machine learning pipelines using Python, Docker, Kubernetes, and AWS.
• Develop real-time and batch processing workflows with Kafka and Airflow.
• Implement solutions with vector databases for retrieval, recommendations, and semantic search functionalities.
• Manage experiments, model versions, and deployments using MLflow.
• Continuously evaluate and improve AI system quality through automated pipelines, benchmarks, and monitoring.
• Monitor AI systems in production, identify improvements, and implement safeguards to ensure data security and system reliability.
• Establish technical standards and best practices for AI development and deployment.
• Collaborate with cross-functional teams to align AI projects with business goals and customer needs.
• Communicate technical concepts effectively to diverse audiences and contribute to strategic planning for AI initiatives.

Qualifications and Skills

• At least four years of experience in building and deploying machine learning or AI systems in a production setting.
• Strong skills in Python programming and software engineering principles.
• Experience developing production services with frameworks like FastAPI.
• Hands-on experience with generative AI, large language models, RAG, or agentic systems.
• Familiarity with frameworks such as PyTorch, LangChain, or LangGraph.
• Deep understanding of enterprise RAG systems, including retrieval, chunking, embeddings, and evaluation techniques.
• Experience creating automated evaluation pipelines for AI models.
• Proficiency with AWS services, Docker, Kubernetes, Terraform, and CI/CD practices.
• Experience managing ML workflows with MLflow and monitoring tools like Datadog or OpenSearch.
• Knowledge of real-time data processing technologies such as Kafka and vector databases.
• Ability to make balanced technical decisions considering quality, speed, reliability, scalability, and cost.
• Excellent communication skills and experience working collaboratively across technical teams.

Additional Preferred Experience

• Experience working within a B2B SaaS environment.
• Familiarity with orchestration tools like Airflow or Argo Workflows.
• Knowledge of SQL, Spark, Snowflake, or similar data processing platforms.
• Experience integrating structured and unstructured data with generative AI systems.
• Understanding of AI security, privacy, responsible AI practices, prompt injection mitigation, and data leakage prevention.
• Experience optimizing latency and reducing costs for AI systems at scale.

Company Culture & Diversity

Typeform values diversity and is committed to creating an inclusive environment. They celebrate individual perspectives and foster a culture grounded in respect, transparency, and trust. The company is an equal-opportunity employer, welcoming applicants regardless of race, religion, gender, age, sexual orientation, disability, or veteran status. They prioritize addressing the needs of their diverse customer base and continuously strive for excellence in their work.

Degree Requirement: Not Specified

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