Senior AI Engineer

This is a fully remote position, open to applicants in United Kingdom, +5 more countries.

📋 Description

• Design, develop, and implement generative AI functionalities across Typeform’s offerings.

• Create applications utilizing large language models, retrieval-augmented generation (RAG), vector search, and agent-based systems.

• Develop services and APIs to integrate AI features into customer interactions.

• Transform prototypes into dependable production systems with quantifiable performance and quality metrics.

• Architect and manage machine learning services and workflows employing Python, Docker, Kubernetes, and AWS.

• Construct batch and real-time processing pipelines using technologies like Kafka and Airflow.

• Design vector-database solutions for tasks such as retrieval, recommendations, personalization, and semantic search.

• Oversee experiments, model versions, registries, and deployments through MLflow.

• Develop automated evaluation pipelines and benchmarks to ensure generative AI quality.

• Assess retrieval strategies encompassing chunking, embeddings, context selection, and reranking.

• Monitor operational AI systems to enhance quality, performance, reliability, scalability, and cost-effectiveness.

• Implement safeguards to protect customer data and minimize unforeseen behavior.

• Establish reusable AI engineering patterns and technical standards.

• Collaborate with Product, Engineering, Data Science, Data Engineering, and Analytics teams.

• Convert experiments and models into consistent production services.

• Contribute to technical planning and influence Typeform’s AI strategy.

• Share technical expertise and provide support to fellow engineers.

⛳️ Requirements

• Minimum of four years of experience in building and deploying machine learning or AI systems in a production environment.

• Proficient in Python and software engineering principles.

• Experience developing production services with Python frameworks such as FastAPI.

• Hands-on experience in creating generative AI applications utilizing large language models, RAG, tool usage, or agent-based systems.

• Familiarity with frameworks like PyTorch, LangChain, LangGraph, or comparable technologies.

• Strong knowledge of enterprise RAG systems, including chunking, embeddings, retrieval, reranking, evaluation, and monitoring.

• Experience in creating automated evaluations for generative AI applications.

• Proficient with AWS, Docker, Kubernetes, Terraform, and practices related to continuous integration and deployment.

• Experience using AWS SageMaker or AWS Bedrock.

• Knowledge of Kafka, vector databases, or technologies utilized for real-time and high-dimensional data processing.

• Experience managing machine learning workflows using MLflow.

• Familiarity with monitoring production systems through tools like Datadog or OpenSearch.

• Ability to balance quality, speed, reliability, scalability, and cost in technical decisions.

• Excellent communication skills and a proven track record of collaborating with Product, Engineering, and Data teams.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health and wellness benefits.

• Opportunities for professional growth and development.

• Flexible work hours and remote working options.

• Collaborative and innovative work environment.