Principal AI Engineer

CNA • Chicago, IL

2d • Hybrid

About The Position

Individual contributor providing the highest level of leadership in AI-native engineering, agentic system design, and applied AI solution development across CNA's Underwriting and Operations portfolio. This position has a deep understanding of AI engineering platforms, large language model (LLM) tooling, and enterprise software delivery from an end-to-end perspective. The focus of this position is designing and scaling AI-enabled solutions that integrate into underwriting workflows, drive measurable business impact, and establish durable AI engineering practices across the organization.

Requirements

• Expert knowledge of AI-native engineering practices, including agentic system design, LLM integration, multi-agent orchestration, and context engineering.
• Deep understanding of enterprise software delivery, including CI/CD pipelines, automated quality gates, cloud-native architecture, and production-grade system design.
• Strong ability to translate complex business workflows — particularly in commercial insurance underwriting — into reliable, scalable AI-enabled solutions.
• Demonstrated ability to advise on AI governance, model explainability, and regulatory compliance considerations in high-stakes or regulated environments.
• Excellent analytical and problem-solving skills with the ability to evaluate build-vs-buy trade-offs and make sound architectural recommendations.
• Proven ability to mentor and develop engineering talent, raising organizational capability in emerging AI practices.
• Excellent communication and interpersonal skills with the ability to engage effectively with peers, technical leadership, and non-technical business stakeholders.
• Working knowledge of the commercial insurance underwriting lifecycle, including submission intake, risk triage and appetite matching, underwriting analysis, and quote-to-bind processes.
• Ability to translate underwriting judgment and business rules into AI-driven insights, model features, decision frameworks, and explainable outputs that can be trusted and adopted by underwriters.
• Familiarity with regulatory and governance considerations impacting AI in insurance, including auditability, transparency, and appropriate use of AI in decisioning.
• Bachelor's degree in Computer Science, Engineering, or a related field; Master's degree preferred.
• Typically a minimum of 10 years of software engineering experience, with at least 3 years in a principal, staff, or architect-level role.
• Demonstrated experience designing and deploying agentic AI systems or AI-native developer platforms in production environments.

Nice To Haves

• Experience in commercial insurance or financial services, with familiarity in underwriting lifecycle processes, preferred.
• Applicable certifications in AI, cloud, or related disciplines preferred.

Responsibilities

• Leads the scaling of AI solutions within the Underwriting portfolio, ensuring AI capabilities developed in product pods are industrialized into reliable, reusable, enterprise-grade services that integrate seamlessly into underwriting and operations workflows.
• Partners closely with underwriting, operations, and product teams to translate domain-specific workflows into AI-enabled solutions — including submission intake, risk triage, data enrichment, pricing signals, and decision support — ensuring alignment to real-world underwriting processes and measurable business impact.
• Designs AI integration patterns across core underwriting and operations systems — including underwriting workbench platforms and document processing pipelines — ensuring solutions are performant, scalable, and embedded directly into decisioning workflows.
• Acts as a senior technical mentor, developing engineers across the organization in AI-native practices including agentic coding patterns, context engineering, prompt-to-code workflows, and AI-assisted testing.
• Builds durable, self-sustaining team capability without ongoing coaching dependency.
• Establishes patterns for AI governance, explainability, and auditability in underwriting use cases, ensuring AI-driven decisions meet regulatory, compliance, and internal risk management expectations.
• Drives reusability and cross-business-unit scalability of AI solutions, designing capabilities that can be leveraged across underwriting segments while accounting for differences in data, workflows, and risk profiles.
• Researches, evaluates, and recommends AI engineering tools, frameworks, and infrastructure (e.g., eval platforms, agent orchestration systems, environment provisioning automation), supporting build-vs-buy decisions with a focus on long-term scalability and maintainability.
• May perform additional duties as assigned.

Benefits

• CNA offers a comprehensive and competitive benefits package to help our employees – and their family members – achieve their physical, financial, emotional and social wellbeing goals.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal