Senior AI Solutions Architect

At Coaction, we’re a unique mix of leaders, achievers, thinkers, and team players with a high-performance mindset and a diverse skillset. We bring our industry expertise together to continually push the boundaries of what insurance can be for our clients.

At Coaction, we're a unique mix of leaders, achievers, thinkers, and team players with a high-performance mindset and a diverse skillset. We bring our industry expertise together to continually push the boundaries of what insurance can be for our clients.

At Coaction, innovation is key to our continued success and growth. As we expand our digital and data capabilities, Artificial Intelligence will play a critical role in enhancing underwriting, operations, and customer experience. We believe the best solutions happen when product, engineering, data, security, and the business partner as one integrated team
-open to ideas, ready to challenge the status quo, and focused on delivering measurable outcomes in a regulated industry.

This is our first dedicated Senior AI Solutions Architect role. This role will be instrumental in defining the technical vision and architecture for how we design, build, deploy, and operate AI-powered solutions safely and responsibly across the enterprise. The ideal candidate is a pragmatic, hands-on architect with an extensive track record of senior technical leadership—focused on translating business strategy into scalable, secure, production-grade AI architecture (not research-only)—and comfortable establishing the repeatable patterns, reference architectures, and guardrails that engineering teams will build on.

This role carries a high degree of autonomy and is expected to shape AI strategy at the executive level, not just execute against it.

Responsibilities Define and own the enterprise AI reference architecture, including patterns for LLM/ML integration, RAG pipelines, and Agentic AI platforms, ensuring alignment with enterprise architecture and security standards.

Architect secure integration patterns for external AI services (LLMs and ML APIs), including data handling, access controls, and auditability, and guide engineering teams in implementing them.

Design retrieval-augmented generation (RAG) architectures for document-heavy workflows (e.g., submissions, endorsements, claims documentation) that scale across multiple enterprise data sources.

Lead the design and rollout of an Agentic AI platform reference architecture, partnering with Architecture and Engineering on implementation.

Define and govern reusable AI components and platform building blocks that accelerate delivery across multiple use cases.

Partner with architecture, engineering, data, and business stakeholders—including senior leadership—to translate strategic needs into solution designs, technical requirements, and delivery roadmaps.

Establish enterprise-wide AI engineering standards for testing and evaluation (quality, safety, regression testing), and guide their integration into CI/CD pipelines.

Define the architecture for monitoring and observability of AI solutions (latency, cost, quality signals, guardrail events) and establish operational runbook standards.

Lead AI governance efforts including vendor/model intake, risk reviews, architecture documentation, and change management processes.

Set security architecture standards for AI systems, including safeguards against prompt injection, data leakage, and misuse.

Author architecture decision records, reference designs, and technical documentation; lead knowledge transfer to broaden internal capability and reduce reliance on external partners over time.

Mentor engineers and junior architects on AI engineering best practices, and serve as the internal escalation point for complex architectural…