VP Architect, AI & Platform

CCC Intelligent Solutions•Chicago, IL

3d•$217,237 - $300,000

About The Position

CCC 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. The Chief Architect, AI & Platform will be responsible for setting CCC’s enterprise-wide technical architecture vision and ensuring that our platforms, products, data systems, AI capabilities, and engineering practices scale together. This leader will partner closely with Product, Engineering, Data Science, Security, Infrastructure, Client Success, and executive leadership to translate business strategy into a durable technical architecture. The ideal candidate is a hands-on strategic technologist who can move fluidly from board-level technology strategy to deep technical design conversations with principal engineers, AI researchers, platform teams, and product leaders. This is a role for someone who understands modern SaaS platforms, AI-native product development, event-driven systems, high-scale data architecture, enterprise integration, and the operational discipline required for trusted automation in regulated, mission-critical environments.

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.
A track record of balancing innovation with reliability, security, customer trust, and business outcomes.

Nice To Haves

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.

Responsibilities

Define and evolve CCC’s long-term architecture strategy across multiple cloud platforms, product domains, data platforms, APIs, integration patterns, AI/ML systems, and developer experience.
Ensure that architectural choices support CCC’s growth, customer trust, speed of innovation, operational resilience, and ability to scale AI-enabled workflows across the insurance economy.
Establish clear architectural principles and decision frameworks that help teams move faster while avoiding unnecessary fragmentation, duplication, and technical debt.
Guide CCC’s transition from software that uses AI to a platform that is increasingly AI-native. This includes architecture for predictive AI, computer vision, generative AI, agentic workflows, human-in-the-loop decisioning, model orchestration, evaluation frameworks, AI observability, model governance, and safe automation.
Help ensure CCC can deploy AI responsibly across high-consequence workflows such as damage assessment, estimating, claims routing, injury prediction, subrogation, total loss prediction, and customer communications.
Lead the architecture for CCC’s data foundation, including data products, event streams, metadata, lineage, governance, data contracts, lakehouse/warehouse patterns, real-time decisioning, and customer-facing analytics.
Turn CCC's ecosystem data advantage into reusable platform capabilities while maintaining privacy, security, accuracy, and customer trust.
Partner with data science and product teams to make CCC’s proprietary data, workflow context, and ecosystem signals easier to use in AI models, product experiences, partner integrations, and internal decision systems.
Guide the evolution of CCC’s multi-tenant SaaS architecture, cloud infrastructure, service boundaries, APIs, event-driven systems, integration patterns, and shared platform capabilities.
Help engineering teams make smart decisions about build vs. buy, modularity, service ownership, resilience, latency, cost efficiency, and operational maturity.
Build an architecture function that enables teams rather than slows them down. This includes creating lightweight governance, architecture review practices, reusable patterns, reference implementations, decision records, and technical roadmaps.
Mentor principal engineers and architects, raise the technical bar across engineering, and help create a culture where architecture is practical, measurable, and connected to business outcomes.
Partner with Security, Legal, Compliance, and Product to ensure CCC’s AI and platform architecture is secure, explainable where needed, auditable, privacy-aware, and resilient. This includes modern AI risk controls such as prompt-injection defenses, secure model supply chains, output validation, data leakage prevention, model monitoring, and human oversight.