Remote AI Engineer

CCC) is a leading cloud platform for the multi-trillion-dollar insurance economy

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creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. We’re pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair journey. CCC) is a leading cloud platform for the multi-trillion-dollar insurance economy, creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. We’re pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair journey. You will own LLM-powered systems and agentic workflows for our customers. These systems automate the routine parts of a claim and guide customers on the rest, so they have to earn that trust with a measured accuracy you can defend as models change and usage grows. Agentic coding tools are how you move fast. What you add is what they are worst at: system architecture, code quality, security, and the debugging nobody else gets to the bottom of. You own a product area end to end and define the eval bar it ships against.

Own the delivery of LLM-powered systems in Python and TypeScript, from an ambiguous customer problem, scoped with product managers and data scientists, through production operation.

~ Set the evals and guardrails strategy for your area: what gates a release, what production signals the team watches, and how a change is simulated against historical claims before it ships.

~ Raise the bar for how the team works with agentic coding tools: sharpen the specifications, instruction files, hooks, and permission policies they run under, and hold generated code to the same review standard before it merges.

~ Design the NLP pipelines that turn unstructured claim data into structured data customers can act on, choosing where semantic search, classical NLP, or an LLM fits.

~ Set the privacy and security baseline every system in your area starts from: tenant isolation, least-privilege access for agents and their tools, redaction, retention, and what data may reach a model provider.

~ Author the design documents for complex systems to get feedback and buy-in, review other engineers designs and code with the same care, and mentor the engineers in your area.

~ Take part in a shared on-call rotation for the systems you own.

6+ years of professional software engineering experience, including an LLM-powered system you architected, shipped to external customers, and carried through at least one model or prompt migration.

~ Python and TypeScript at the level of setting a teams conventions: the async model, typing strictness, and test strategy for a shared codebase, plus a performance problem you profiled and fixed.

~ A clear account of how you constrain an agentic coding tools context and verify its output, from daily use of Claude Code, Cursor, GitHub Copilot, or similar on production work, plus changes you turned back, and why.

~ Pipelines you designed that blend LLMs, semantic search, and classical NLP, including a retrieval design you can defend and a case where a classical technique beat an LLM on cost, latency, or reliability.

~ Data modeling and development across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including when each type fits and the partition-key, consistency, and tenant-isolation calls you made.

~ Systems architected and operated on Azure or AWS, with CI/CD and infrastructure as code, and hands-on time with a durable workflow engine such as Temporal or the Durable Task Scheduler.

~ Technical design documents you have authored for systems that span more than one team, used to get feedback and buy-in before building, and that those teams then built to.

~ Clear writing and discussion for technical and non-technical audiences: drawing out a customers real problem and explaining the trade-offs back to them.

React and TypeScript experience, so you can deliver a full-stack feature end to end, especially chat, streaming, and citation-heavy AI experiences.

~ Experience with agent frameworks, LangGraph, PydanticAI, and the Microsoft Agent Framework among them, and with the ways agents reach their tools: the Model Context Protocol (MCP), the Agent2Agent (A2A) protocol, command-line tools, and microservices.

~ Experience designing A/B tests for AI features.

~ Exposure to the insurance, claims, or automotive repair domains.

In your first six months, every model change in your area is gated by evals you designed, regressions are caught before a customer sees them, and you can show the accuracy number held or moved.

~ You are trusted with the high-stakes, ambiguous problems, and you turn them into a roadmap, a shipped system, and a number you can put in front of a customer.

~ You are energized by what agentic coding tools make possible. Your team ships more than its headcount suggests, and your specifications and reviews are why the output survives production.

~ Standards you set for evals, reviews, and design documents outlive the project they started on.

~ Engineers you mentor ship LLM-powered features with evals and guardrails in place without your direct involvement.

~ You enjoy getting a product manager, a data scientist, and a customers team into one room and coming out with a single agreed scope, and you can argue a position without needing to win it.

~ Interview Policy & Privacy Notice:
A video interview is required for this position. Video interviews are transcribed. Transcriptions are retained and may be reviewed by CCC and our recruiters. Candidates are not permitted to use generative AI or automated assistance during the interviews unless explicitly allowed by the interview team for a specific exercise. Our team is defined by our values of Integrity, Customer-Focus, Innovation, Inclusion & Diversity, Tenacity, and Connection. Annual Incentive Plan Performance Bonus
~ Comprehensive health insurance
~ Tuition Reimbursement
~ Stock Purchase Plan options
~ For more information about our benefits, please check out our careers site.
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