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.
About CCC's Commitment to Employees
CCC Intelligent Solutions understands that our employees play an integral role in our vision to shape a world where life just works. Our team is defined by our values of Integrity, Customer-Focus, Innovation, Inclusion & Diversity, Tenacity, and Connection. Through diverse perspectives, purposeful innovation, and the strength of connections, our technologies empower the people and industry relied upon to keep lives moving forward when it matters most.
At CCC, together everyone can thrive as we innovate and collaborate, creating employee experiences that just work. We are committed to providing opportunities for our people to make real-life impacts, advance in their careers, and contribute to CCC’s success.
CCC offers competitive compensation and benefits to support you and your families, including:
401K Match
Paid time off
Annual Incentive Plan Performance Bonus
Comprehensive health insurance
Adoption Assistance
Tuition Reimbursement
Wellness Programs
Stock Purchase Plan options
Employee Resource Groups
For more information about our benefits, please check out our careers site.
Here, you belong. You are seen, valued, and respected. We celebrate you for who you are and all you bring. Every voice is heard and is important to our success. You can hear what employees have to say about our culture here
