ccc-intelligent-solutions

CCC Intelligent Solutions Software Engineer Case Interview — Photo-to-Estimate System Design

This case mirrors CCC Intelligent Solutions’ real-world domain and interview style: a collaborative, project-focused technical discussion with light coding/architecture depth. You’ll be asked to design a service that ingests accident photos and returns a line‑level damage estimate, integrating AI scoring and insurer rules (akin to CCC Estimate–STP), while addressing scale, latency, security, and observability. Expect interviewers to probe tradeoffs (event-driven vs. synchronous flows), multi-tenant concerns, idempotency, data retention for PII, and fallbacks to human review. The tone is conversational and resume-anchored, reflecting CCC’s typical interviews, which often include LeetCode‑style easy/medium questions and, for some roles, online SQL/Python screens; panels or multi-interviewer sessions are common. The case also touches on CCC’s culture and values—customer focus, integrity, innovation, inclusion & diversity, tenacity, and connection—so be ready to align design decisions to measurable claim-cycle improvements and user impact. Structure (suggested): 1) Clarify requirements and success metrics (e.g., p95 latency < 5s, straight‑through‑processing rate, cost/claim). 2) APIs, data model, and storage choices (object store for images, metadata DB, feature store). 3) High-level architecture (ingestion gateway, validation, rules engine, AI inference, workflow/orchestration; queueing and retries). 4) Reliability, scaling, and cost controls (autoscaling inference, canary/A‑B, backpressure). 5) Privacy/compliance, auditability, and access controls. 6) Extensibility (adding First Look/Impact Dynamics-style early decisioning; integrating repairers). Expect light whiteboarding/pseudocode (e.g., idempotent upload handler or rate limiter) plus behavioral questions about past projects and teamwork. Sources indicative of CCC’s interview and product context: interviews noting collaborative tone, coding (easy–medium) and panels; systems/SQL/Python screens; and CCC’s AI photo-estimating products and values. ([glassdoor.com](https://www.glassdoor.com/Interview/CCC-Intelligent-Solutions-Interview-Questions-E4574.htm?utm_source=chatgpt.com), [cccis.com](https://www.cccis.com/insurance-carriers/claims-solutions/apd/repair-management/estimate-stp?utm_source=chatgpt.com), [ir.cccis.com](https://ir.cccis.com/news-releases/news-release-details/ccc-introduces-next-generation-ai-based-photo-analysis?utm_source=chatgpt.com))

engineering

8 minutes

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About This Interview

Interview Type

PRODUCT SENSE

Difficulty Level

3/5

Interview Tips

• Research the company thoroughly

• Practice common questions

• Prepare your STAR method responses

• Dress appropriately for the role