Senior AI Engineer (Casualty / Claims Intelligence)

CCC Intelligent Solutions•Chicago, IL

About The Position

CCC Intelligent Solutions is hiring a Senior AI Engineer to build AI-native products for its auto casualty business, which focuses on the injury side of auto claims. The engineer will own AI agents end to end within a problem area, from prototyping through measured performance in production, as part of a small, growing, senior engineering group. The team works on AI products that help claims teams process medical bills accurately and efficiently, support better and faster claims decisions, and provide an agentic rules platform and evaluation infrastructure. The engineer will build agents that work with complex documents and claim data, use tools, and support claims experts. The role owns agent orchestration, retrieval, evaluations, and guardrails, as well as the production code needed 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, backed by evaluation results, within six months. The position is bonus eligible, with a stated salary range of $180,000–$225,000.

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 shipping LLM-powered products to real users, including retrieval methods such as RAG, embeddings, or vector search, and prompt engineering.
Experience designing evaluations for non-deterministic systems and measuring before and after every change.
A quantitative mindset, including comfort with metrics, sampling, error analysis, and determining whether a result is 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 in collaboration with data labelers and subject matter experts, and run evaluations 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 within a problem area, from prototype through measured performance in production.
Write production code to ship AI agents and products.