Federato is on a mission to defend the right to efficient, equitable insurance for all. We enable insurers to provide affordable coverage to people and organizations facing the issues of today - the climate crisis, cyber-attacks, social inflation, etc. Our vision is understood and well funded by those behind Salesforce, Veeva, Zoom, Box, etc.

Federato is the only AI-native platform that spans the full policy lifecycle and changes the way insurance work gets done. Better decisioning is built-in, not bolted on: insurers' unique portfolio goals, strategies, rules, and appetite are part of the workflow so underwriters win the right deals, faster. From the moment a submission hits an underwriter’s inbox, AI is put to work, triaging submissions with a focus on high-appetite business, delivering real-time feedback on the portfolio, and consolidating workflows into a single proven system. Federato drives better business outcomes.

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.
Strong proficiency in SQL and Python, with bonus points for Typescript (or similar) experience
Comfort working with version control, CI/CD systems, and cloud infrastructure (e.g., AWS, GCP, Terraform).
Comfortable navigating ambiguity and working closely with business stakeholders to understand their data needs.
Proven track record of designing high-impact data products and pipelines in fast-paced environments.

Bonus Points for:

Prior experience working in or adjacent to insurance, fintech, or risk modeling domains.
Prior exposure to ML ops or experience supporting AI/ML-driven products
Enthusiasm for building internal tools or frameworks to improve team velocity.
Contributions to open-source data tools or involvement in the data community.

$160,000 - $210,000 a year
Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above. Total compensation package does include stock options, benefits and additional perks.

Here at Federato, your capabilities are important, but culture fit is essential. We move fast, are eager to listen to our users, take a first principles approach to solving problems, and value learning and the ability to change our minds. Most importantly, we're here to have fun. Our ability to make a difference starts with our people. We would love to work with you!

We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender expression, sexual orientation, age, marital status, veteran status or disability status. We will provide reasonable accommodation to individuals with disabilities to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation at talent@federato.ai

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.
Strong proficiency in SQL and Python, with bonus points for Typescript (or similar) experience
Comfort working with version control, CI/CD systems, and cloud infrastructure (e.g., AWS, GCP, Terraform).
Comfortable navigating ambiguity and working closely with business stakeholders to understand their data needs.
Proven track record of designing high-impact data products and pipelines in fast-paced environments.

Bonus Points for:

Prior experience working in or adjacent to insurance, fintech, or risk modeling domains.
Prior exposure to ML ops or experience supporting AI/ML-driven products
Enthusiasm for building internal tools or frameworks to improve team velocity.
Contributions to open-source data tools or involvement in the data community.

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