VP Architect, AI & Platform
CCC Intelligent Solutions · Chicago, IL · Yesterday
HybridArt & Creative$217k/yrFull-time
Key Responsibilities
- Technology Vision and Architecture Strategy
- AI-Native Platform Architecture
- Data Architecture
- Platform Modernization and Scalability
- Architecture Operating Model
- Security, Trust, and Responsible AI
Requirements
- 15+ years of technology experience, including significant leadership experience in SaaS, platform architecture, enterprise software, data-intensive systems, or AI-enabled products.
- Proven experience architecting large-scale, cloud-native, multi-tenant platforms used by enterprise customers.
- Deep understanding of distributed systems, event-driven architecture, APIs, microservices or modular monolith patterns, cloud infrastructure, security, observability, and reliability engineering.
- Strong experience with data architecture, including real-time data, analytics platforms, data governance, metadata, data quality, and data products.
- Practical understanding of AI/ML systems, including model lifecycle management, MLOps/LLMOps, generative AI patterns, evaluation, monitoring, responsible AI, and human-in-the-loop workflows.
- Experience influencing across large engineering organizations without relying only on formal authority.
- Ability to communicate architecture tradeoffs clearly to executives, product leaders, engineers, customers, and non-technical stakeholders.
- Track record of balancing innovation with reliability, security, customer trust, and business outcomes.
Preferred Qualifications
- Experience in insurance, automotive, collision repair, fintech, healthcare, logistics, or another complex workflow-heavy industry.
- Experience building platforms that support marketplaces, partner ecosystems, or multi-party networks.
- Experience with computer vision, claims automation, document intelligence, decision automation, or workflow orchestration.
- Experience modernizing legacy platforms while continuing to support large enterprise customers.
- Familiarity with AI governance frameworks, model risk management, privacy requirements, secure software development, and regulated-industry expectations.
- Experience working with public-company technology, security, and operating expectations.