Principal AI Scientist

Palomar•La Jolla, CA

About The Position

Palomar is hiring a Principal AI Scientist to shape how AI is applied, scaled, and enabled across the company. The role combines scientific depth, hands-on engineering, and business judgment. Reporting to the EVP, Head of AI, the Principal AI Scientist will write code, own AI architecture and standards, and help develop the team as the program grows. The initial focus is establishing an enterprise AI foundation: representing company knowledge so agents can use it, building a governed library of skills, plugins, and connectors, and enabling employees to build safely on the platform. The role will set scientific standards for evaluating retrieval, testing agents, and measuring outcomes. As internal owners take on day-to-day platform operations, the role will expand into predictive modeling, machine learning, and strategic decision support for business leaders.

Requirements

Master’s or PhD in computer science, statistics, machine learning, operations research, or a related field, or equivalent experience.
8+ years shipping machine learning or AI systems in production, including recent hands-on work with LLM applications such as agents, retrieval, tool integration, and evaluation.
Experience building a platform or shared tooling adopted by other teams, with evidence of that adoption.
Strong statistics and experimental design skills, with the judgment to distinguish predictive accuracy from business impact.
Hands-on depth in supervised and unsupervised learning, feature engineering, and model validation, including data leakage, uncertainty, and drift.
Strong Python, SQL, and software engineering fundamentals, including APIs, Git, testing, CI/CD, and cloud.
Willingness and ability to write code as part of the role.
Ability to frame ambiguous problems with domain experts, explain tradeoffs clearly to executives and engineers, and help non-engineers build effectively with AI.
Demonstrable track record of working autonomously and driving progress.
Intellectual curiosity, creative thinking, and pragmatism.

Nice To Haves

Insurance or financial services experience, especially in underwriting, operations, or claims.
Experience with forecasting, optimization, causal inference, or decision science.
Experience operating an enterprise LLM platform at company scale.
Model risk management or AI governance experience in a regulated industry.

Responsibilities

Own the technical direction and operation of the enterprise AI platform, including models, permissions, connectors, reliability, and cost.
Build a governed marketplace of reusable skills and plugins that employees can contribute to or use within their permissions.
Turn Palomar’s procedures and expert know-how into version-controlled context that agents can use reliably, connected to trusted data and core systems.
Set evaluation and release standards, including test cases, acceptance criteria, accountable owners, and monitoring for everything that ships.
Advise AI leadership on which tools to build, buy, improve, or retire.
Lead enablement through training, office hours, and reviews of employee-built solutions, and develop internal owners for those solutions.
Work with business experts to capture judgment and exceptions and turn effective practices into tested, reusable capabilities.
Shape the applied AI agenda with business leaders, prioritizing work by value, feasibility, data readiness, and risk.
Develop, validate, and deploy predictive models and decision support for problems such as prioritization, routing, portfolio, and distribution.
Choose statistical, machine learning, or LLM methods as appropriate, with clear boundaries for automation and human review.
Measure decision quality and business impact against real baselines, monitor deployed solutions, and work with Risk and Compliance to ensure alignment with Palomar’s AI policies.