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Senior Data Engineer, Insurance AI/ML

Federato

New This Week
ML EngineeringInsuranceSenior (6-10 yrs)RemoteInsurance

Build the data infrastructure powering AI-driven insurance underwriting at Federato β€” enabling ML engineers to deploy models for risk assessment and claims automation.

AI β†’ Finance

Location

Remote

Salary Range

$170,000 – $210,000

Posted

Mar 28, 2026

Insider Signals

Beta
⚑Growing AI Team

Federato is in the growing stage of its AI organization. Great time to join.

πŸ“ŠActive Hiring

Federato has had 5 hiring events in the last 30 days β€” they're actively building.

Company AI Context

AI Maturity

growing

Tech Stack

pythonsqletl-pipelinesairflowawsterraform

Join Federato's AI/ML organization to build infrastructure and frameworks enabling ML engineers to develop and deploy AI-powered features for insurance underwriting.

## About the Role Join Federato's AI/ML organization to build infrastructure and frameworks enabling ML engineers to develop and deploy AI-powered features for insurance underwriting. Develop scalable frameworks for prompt engineering pipelines and AI workflows, from LLM workflows to traditional model-driven systems. Fully remote with $170K-$210K salary plus stock options. ## Responsibilities - Build data infrastructure for ML engineers - Develop ETL pipelines using Airflow, Dagster, or Prefect - Create scalable frameworks for AI/ML workflows - Support prompt engineering pipelines and LLM deployment - Ensure data quality and reliability across the platform ## Requirements - 5+ years in data engineering, backend engineering, or infrastructure - Proficiency in SQL and Python - Experience with ETL tools (Airflow/Dagster/Prefect) - Cloud infrastructure experience (AWS/GCP/Terraform) - CI/CD experience - Insurance/fintech domain experience a bonus

Skills & Technologies

pythonsqletl-pipelinesairflowawsterraformdockerdata-engineering

Best Backgrounds

  • machine learning engineering
  • software engineering
  • data engineering
  • applied mathematics

Related Titles to Explore

  • ML Engineer
  • Applied Scientist
  • ML Platform Engineer
  • AI Engineer

Career Bridge Playbook

Beta

Career paths into this role

software engineer
data engineer
data scientist
research scientist

Where this role leads

ML lead
head of AI
principal engineer
AI research scientist

Transition Difficulty

high

Key Skill Gaps to Close

  • financial domain knowledge
  • regulatory awareness
  • model risk management

Skills used in this role

Technical

pythonsqletl-pipelinesairflowawsterraformdockerdata-engineering

Domain

model-developmentfeature-engineeringmodel-deploymentrisk-modeling

Soft Skills

cross-functional-collaborationtechnical-communicationproblem-solving

Interested in this role?

Apply directly on the company's career page.

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