The RoleCCC 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. Learn more about CCC at www.cccis.com.
Key Responsibilities:You will build the event-driven systems that keep claims moving for our customers, connecting our AI agents to the rest of CCC. When these systems work, claims move faster and the machinery stays invisible. Agentic coding tools are how you move fast. What you add is what they are worst at: distributed-systems design, correctness when things fail partway, and the debugging nobody else gets to the bottom of. You own a product area end to end and define the reliability bar it ships against.
Key Responsibilities:
- Own the delivery of backend services, built in Python and TypeScript, from an ambiguous problem, scoped with product managers and data scientists, through production operation.
- Build and operate durable, event-driven, multi-tenant systems in which agents run as steps inside deterministic workflows, designing their failure modes, replay semantics, and cost profile before they show up under load.
- Own tracing and audit for your area: every model call and agent step recorded, so any recommendation can be reconstructed and cited back to its sources by on-call and auditors alike.
- Own how claims automation data is modeled and managed across our relational, document, and graph stores. Ensure the security and isolation of sensitive data.
- 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.
- 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.
- Take part in a shared on-call rotation for the systems you own.
Requirements:- 6+ years of professional software engineering experience, including an event-driven system you designed, shipped to customers, and ran in production.
- Python and TypeScript at the level of setting a team's conventions, plus a background in a systems language such as Rust, Go, Java, or C#.
- Strong computer science and distributed-systems fundamentals you use at work: concurrency, consistency, ordering, and how systems fail.
- Event-driven systems built on a broker such as Kafka, Azure Event Hubs, or Service Bus that handle duplicate, late, and failed events without losing or double-processing work.
- 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.
- A clear account of how you constrain an agentic coding tool's 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.
- 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 customer's real problem and explaining the trade-offs back to them.
Even Better if You Have:
- React and TypeScript experience, so you can deliver a full-stack feature end to end, especially chat, streaming, and citation-heavy AI experiences.
- Formal methods or fault-injection testing, such as Lean, TLA+, or deterministic simulation.
- Performance work below the application layer: profiling, memory, and concurrency tuning.
- Familiarity with how AI agents reach their tools and enterprise systems, through the Model Context Protocol (MCP), the Agent2Agent (A2A) protocol, command-line tools, and microservices.
- Exposure to the insurance, claims, or automotive repair domains.
What Success Looks Like:
- In your first six months, services you built run in production against SLOs you set, and you can show they held as load grew.
- You are trusted with the hardest correctness and scale problems, and you turn them into a design, 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.
- You have a passion for systems that last: failures are designed for in advance, and when one happens anyway, the trace says exactly where.
- Standards you set for reliability, reviews, and design documents outlive the project they started on.
- Engineers you mentor ship reliable services without your direct involvement.
- You enjoy getting a product manager, a data scientist, and a customer's team into one room and coming out with a single agreed scope, and you can argue a position without needing to win it.
- You embrace our ambitious, collaborative, and empathetic values, and you like problems where the answer has to be measured rather than argued.
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 Job Applicant Privacy Notice is available HERE.
