Remote
Senior Data Engineer
About this role
There's nothing more exciting than transforming an industry that's been stagnant for decades. Federato is an AI-native platform that’s bringing agentic AI to the full policy lifecycle. We’re aggressively transforming how insurance work gets done, and the world is paying attention: we've raised $180 million, including a $100 million Series D from Goldman Sachs. We have powerful product-market fit, and we're growing fast globally.
You'll get to work on complex problems with one of the most advanced AI teams you'll find anywhere. If you're the person we need, you know that AI bolted onto legacy systems is too weak to matter. That's why we built our platform to be AI-native from day one. That's why you can do here what you can never do at a legacy software company. move fast and prove it, not theorize it. We think from first principles. You’ll work on problems that matter, building software that fundamentally changes how insurance operates.
Role Overview You’ll be joining a small, high-impact data engineering team within Federato’s AI/ML organization. Our focus is on building the infrastructure and internal frameworks that empower machine learning engineers to develop, deploy, and iterate on AI-powered features ranging from prompt-based LLM workflows to more traditional model-driven systems. We collaborate closely with ML, analytics, and product teams to ensure data and tooling are reliable, scalable, and aligned with the needs of our AI-native platform.
What You'll Be Doing : Collaborate with Data Science, Product Managers and Software Engineers to build robust ETL pipelines that enable the Product Support team to deliver compelling user-facing features Contribute to architecture decisions, observability tooling, and data quality initiatives that keep our platform robust and maintainable. Contribute to a scalable internal framework for managing prompt engineering pipelines and other AI workflows.
Enforce and elevate engineering best practices across the AI/ML org, including code quality, testing, and documentation. Who We Hope You Are: 5+ years of experience in data engineering, backend engineering, or related roles with a focus on data infrastructure. Proven experience designing and maintaining scalable data pipelines (e.g., using Airflow, Dagster, or Prefect). Experience with software development practices like version control, CI/CD, or dbt testing strategies.