Remote Staff AI Engineer, Research Flow Lead

Remote; San Francisco (CA); Remote; USD 210,000 - 320,000; Full time

Job summary

Typeform is seeking a Staff AI Engineer to shape the technical direction of Research Flow and the AI systems behind our products. You will own complex engineering challenges, connect AI capabilities into reliable customer experiences, and drive architecture across generative AI, enterprise RAG, and model evaluation at scale.

You will lead production ML pipelines, build reusable services, and guide decisions on build vs.

Qualifications

• Significant experience building and operating ML/AI systems in production.
• Track record leading complex engineering initiatives across teams.
• Strong Python and software engineering skills with production code experience.
• Experience designing production services and APIs (e.g., FastAPI).
• Experience with AWS, Docker, Kubernetes and cloud-based infrastructures.
• Experience with ML lifecycle tools and observability for production systems.

Responsibilities

• Shape the technical direction of Research Flow and AI systems.
• Lead architectural decisions across AI-assisted study design and research synthesis.
• Own ambiguous problems from exploration to production delivery.
• Build reusable services and APIs for AI capabilities.
• Define evaluation strategies and release criteria for generative AI applications.
• Mentor engineers and raise engineering standards across teams.

Skills

Python

Software engineering

Production ML/AI systems

Leadership beyond own projects

API design / FastAPI

AWS

Docker

Kubernetes

LangChain / LangGraph

PyTorch

Observability (Datadog/OpenSearch)

Mentoring engineers

Cross-team collaboration

Tools

Docker

Kubernetes

AWS

Terraform

Airflow

Kafka

MLflow

Datadog

OpenSearch

SageMaker/Bedrock

Job description

Typeform is seeking a Staff AI Engineer to shape the technical direction of Research Flow and the AI systems behind our products. You will own complex engineering challenges, connect AI capabilities into reliable customer experiences, and drive architecture across generative AI, enterprise RAG, and model evaluation at scale.

You will lead production ML pipelines, build reusable services, and guide decisions on build vs.