Senior AI Engineer

CCC Intelligent Solutions Inc. (CCC) is a leading cloud platform for the multi-trillion-dollar insurance economy, creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. At CCC, we’re making life just work by empowering more than 35,000 businesses with industry-leading technology to get drivers back on the road and to health quickly and seamlessly.

We’re pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair journey. Through purposeful innovation and the strength of its connections, CCC technologies empower the people and industry relied upon to keep lives moving forward when it matters most.

The Role

As a Senior AI Engineer, you’ll own agents end-to-end within a problem area, from the first prototype to measured performance in production. You’ll join a new engineering group at CCC building AI-native products for our auto casualty business, the injury side of auto claims. The group is small and senior, and it’s growing fast. Our teams work on:

• Medical bills: AI products that help claims teams handle the medical bills on injury claims accurately and efficiently.
• Claims decision support: products that help claims professionals make better, faster decisions on injury claims.
• Agentic Rules Platform: the rules engine and agentic tooling behind decisions across our casualty products, plus the evaluation infrastructure every team relies on.

You’ll build the AI agents behind our products. They work with complex documents and claim data, call tools, and support claims experts in their daily work. You’ll own the orchestration, retrieval, evaluations, and guardrails that make them safe to rely on, and you’ll write the production code to ship them.

Key Responsibilities:

• Design and build LLM-powered agents and workflows: 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: guardrails, observability, cost and latency, and careful handling of sensitive health data.

What success looks like:

• In your first month, you’ve shipped a measured improvement to an existing agent.
• By six months, an agent you built is in production with customers, backed by evaluation results.

Requirements:

• Typically 5+ 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 a year of shipping LLM-powered products to real users, including retrieval (RAG, embeddings, vector search) and prompt engineering.
• Experience designing evaluations for non-deterministic systems, and the habit of measuring before and after every change.
• A quantitative mindset: you’re comfortable with metrics, sampling, error analysis, and knowing when a result is real.
• Real experience shipping faster with AI-assisted or agentic engineering tools, with examples you can walk us through.

Nice to have:

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