Senior AI Engineer (Casualty / Claims Intelligence)

CCC Intelligent Solutions•Chicago, IL

5d•$180,000 - $225,000

About The Position

CCC Intelligent Solutions is hiring a Senior AI Engineer for a new, fast-growing engineering group building AI-native products for its auto casualty business, focused on the injury side of auto claims. The group is small and senior. Its work includes AI products that help claims teams process medical bills accurately and efficiently, claims decision-support products, and an agentic rules platform and evaluation infrastructure used across casualty products. The engineer will own AI agents end to end within a problem area, from prototyping through measured production performance. The agents work with complex documents and claim data, call tools, and support claims experts. The role owns agent orchestration, retrieval, evaluations, and guardrails, as well as the production code required to ship these systems. Success includes shipping a measured improvement to an existing agent in the first month and having an agent built by the engineer in production with customers, supported by evaluation results, within six months.

Requirements

Typically 5 or more years of professional software or ML engineering experience, including meaningful recent work with LLMs.
Strong production engineering skills in Python, including API services, and comfort working in TypeScript.
At least one year of experience shipping LLM-powered products to real users, including retrieval (RAG, embeddings, vector search) and prompt engineering.
Experience designing evaluations for non-deterministic systems and a habit of measuring before and after every change.
A quantitative mindset, with comfort using metrics, sampling, and error analysis and determining whether results are real.
Real experience shipping faster with AI-assisted or agentic engineering tools, with examples to discuss.

Nice To Haves

Experience with document understanding, OCR, or extraction from complex documents.
Experience fine-tuning LLMs or working with multimodal data.

Responsibilities

Design and build LLM-powered agents and workflows, including orchestration, tool use, retrieval, structured extraction, and human-in-the-loop review.
Build evaluations with data labelers and subject matter experts, and run them on every change.
Make agents production-grade through guardrails, observability, cost and latency management, and careful handling of sensitive health data.
Own agents end to end, from initial prototype through measured performance in production.