Director – Data & AI Engineering

Ledgebrook

Director/Senior Director of Data & AI Engineering for insurance startup Ledgebrook. Leading data platform and AI/ML practice with a focus on integration and automation.

Posted 7/1/2026full-timeRemote • California • 🇺🇸 United StatesSenior💰 $200,000 - $250,000 per yearWebsite

Tech Stack

Tools & technologies

AirflowPythonSQLTerraform

About the role

Key responsibilities & impact

Manage, mentor, and grow a 10-person data engineering team and a 3-person AI/ML team; own headcount planning and hiring across both
Set a unified roadmap where data infrastructure and AI/ML development reinforce each other
Build a culture of technical rigor, ownership, and delivery
Lead development of ML models using proprietary insurance data: risk scoring, pricing signals, anomaly detection, loss prediction
Own LLM integration strategy from prompt engineering and RAG pipelines to fine-tuning and agentic workflows
Drive AI automation across operations: underwriting intake, document processing, triage, internal tooling
Partner with the CTO on enterprise AI platform decisions: tooling, deployment infrastructure, model governance
Build the evaluation, monitoring, and feedback loops that turn experiments into production systems
Set architectural standards for pipelines, data modeling, and platform infrastructure
Own reliability, observability, and data quality across Snowflake, dbt, Airflow, and Terraform
Build semantic layers and data models that serve underwriting, pricing, finance, and executive reporting
Establish data governance, quality frameworks, and documentation standards that scale
Collaborate with actuaries, underwriters, engineers, and product leaders to translate business needs into AI and data solutions
Operate as a senior technical voice in planning, roadmap, and strategy discussions

Requirements

What you’ll need

Required 8+ years across data engineering, ML engineering, or AI/data science with meaningful depth in at least two of those
3+ years managing technical teams, with experience leading both data and ML/AI practitioners
Hands-on fluency in Python and SQL; comfort reviewing production ML code and data pipelines
Experience building and deploying ML models against structured business data (pricing, risk, fraud, or equivalent)
Production experience with LLMs - RAG architectures, prompt design, agentic frameworks, or fine-tuning
Strong grounding in modern data stack tooling (Snowflake, dbt, Airflow, Terraform or equivalents)
History of taking AI/ML work from prototype to reliable production system
Experience in insurance, fintech, or other data-rich regulated domains (Nice to Have)

Benefits

Comp & perks

Full remote flexibility and asynchronous work culture
Unlimited PTO and fully paid sick leave
Comprehensive health benefits, including medical, dental, and vision coverage, plus HSA and FSA options
Additional financial protection and retirement benefits, including a 401(k), company-paid life insurance, and disability coverage
A high degree of ownership, autonomy, and the opportunity to help build and shape a growing company
The chance to make a meaningful impact while working alongside an ambitious, high-performing team
Exposure to the challenges and opportunities of a fast-growing startup environment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Data EngineeringMachine Learning EngineeringAI/Data ScienceML Model DeploymentData Pipeline DevelopmentRisk ScoringPricing SignalsAnomaly DetectionLoss PredictionData Modeling

Soft Skills

MentoringCollaborationTechnical LeadershipStrategic PlanningCommunication