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# Staff Software Engineer (Insurance Tech)

- **Company:** EvolutionIQ
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $245,000.0 - $270,000.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), .NET Framework, Artificial Intelligence, C Sharp (Programming Language), Code Review, Information Engineering, Relational Databases, Python (Programming Language), Software Tools, TypeScript, Backend, Legacy Systems
- **Published:** July 23, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f4eb09cf20adf699

## About the Role

* 8+ years of engineering experience, with a track record of owning features end to end: partnering with Product, scoping, designing data models, implementing, and living with the system long-term
 * A strong hands-on coder in our stack: Python primarily, with TypeScript / JavaScript across the front end
 * Deep architectural experience with existing systems, not just greenfield: evaluating, modernizing, and replatforming, including multi-tenant, multi-user backends and solid relational database design
 * Experienced with AI-assisted and agentic engineering tools, and can point to real work you've shipped faster because of them
 * Ask the right questions to understand a customer's business problem, and connect your technical work to business impact
 * A crisp communicator with the emotional intelligence to build trust across teams as we bring EvolutionIQ's work into CCC's auto casualty organization

Nice to Have:

 * C# / .NET experience, since modernizing some of CCC's existing systems may involve it
 * Experience across both startups or scale-ups and larger enterprises, which mirrors the EvolutionIQ-into-CCC nature of this work
 * Familiarity with insurance, claims, or the auto casualty space

## Description

* Architect systems and write the code that makes them real, bringing EvolutionIQ's AI-native products into CCC's auto casualty business
 * Dig into complex, sometimes messy legacy systems; decide what to rebuild, replace, or keep; and drive that work hands-on
 * Build backend architectures that hold up in production, moving between fast prototypes and stable, long-lived systems, with AI and agentic tools core to how you work
 * Set the engineering standard (best practices, design docs, code reviews, consistency) in close partnership with Product, Data Science, and Data Engineering


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