Principal AI Engineer

At CNA Insurance, this Principal AI Engineer role is an individual-contributor position focused on the highest level of technical leadership for an AI-native agentic engineering platform. You will help shape foundational platform capabilities that enable safe, scalable delivery across the enterprise, with strong emphasis on quality and security guardrails.

Working in a hybrid setup from Chicago, IL, you will partner across engineering and supporting functions to design, integrate, and scale AI-augmented engineering workflows that fit real delivery lifecycle requirements. The role offers a base salary range of USD 97,000 - 189,000 per yearly.

What you will do

• Serve as one of the principal engineers for CNA’s AI-native engineering platform, owning end-to-end design across agentic coding workflows, skills and agent marketplaces, AI-augmented CI/CD pipelines, automated quality gates, and rapid environment provisioning.
• Lead integration of AI tooling into the software delivery lifecycle, including Claude Code, Cursor, and GitHub Copilot, so the capabilities work together within a coherent, governed platform.
• Design and build the agentic infrastructure layer, including multi-agent orchestration patterns, sub-agent frameworks, skill authoring standards, and context engineering best practices.
• Provide expert technical consultation to engineering leadership, portfolio teams, and architecture on adopting AI-native development practices, evaluating AI-generated code quality, and integrating agentic tooling into existing workflows.
• Advise on trade-offs between speed and quality, human-in-the-loop requirements, and appropriate AI autonomy levels based on risk profiles (for example, SOX-classified systems vs. rapid prototyping).
• Lead technical strategy for the centralized skills and agent marketplace, defining contribution standards, review processes, and governance models that support inner-source contribution while meeting enterprise quality and security requirements.
• Establish enterprise-level definitions for what qualifies as a skill, an agent, and an MCP configuration.
• Act as a senior technical resource, mentoring engineers across the organization on AI-native engineering practices such as agentic coding patterns, context engineering, prompt-to-code workflows, and AI-assisted testing.
• Research, evaluate, and recommend AI engineering tools, frameworks, and infrastructure aligned with CNA’s strategic direction, including eval platforms, agent orchestration systems, and environment provisioning automation.
• Lead build-vs-buy decisions for platform capabilities including CI/CD tooling, sandbox provisioning, and LLM evaluation infrastructure.
• Work closely with Architecture, Security, Cloud Engineering, and Data teams to integrate the platform with enterprise infrastructure (including GCP/GKE, GitHub, and JFrog Artifactory), meet regulatory and compliance requirements (including AI model tracking and SOX controls), and scale to support hundreds of engineers and AI pod teams across portfolios.

Requirements

• Expert knowledge of AI-native software engineering practices, including agentic coding workflows (Claude Code, Cursor, GitHub Copilot), prompt and context engineering, multi-agent orchestration, MCP protocol, and skill/agent authoring patterns.
• Deep understanding of the modern software delivery lifecycle, including how AI transforms each phase from AI-assisted requirements and design through agentic code generation, automated testing, AI-augmented code review, and continuous deployment.
• Expert-level proficiency building and operating CI/CD platforms (GitHub Actions or equivalent), infrastructure-as-code (Terraform), container orchestration (GKE/Kubernetes), and cloud platforms (GCP), with experience creating pipelines that enforce quality and security gates without slowing delivery.
• Strong knowledge of application security engineering, including supply chain security, artifact management and curation, static/dynamic analysis, secret management, and threats introduced by AI-generated code (including dependency hallucination, model drift, and prompt injection).
• Demonstrated ability to design developer platforms and tooling serving hundreds of engineers at varying skill levels, balancing capability with guardrails that prevent misuse and maintain code quality at scale.
• Proven ability to evaluate and integrate emerging AI technologies quickly, with strong judgment about what is production-ready.
• Excellent communication skills for translating complex AI engineering concepts to technical and non-technical audiences.
• Ability to influence engineering culture and drive adoption of new practices across large, diverse organizations, including internal teams and managed service providers.
• Strong analytical and problem-solving skills with an outcomes-oriented mindset focused on measurable improvements in delivery speed, code quality, and engineering productivity.

Technologies

• Claude Code, Cursor, GitHub Copilot
• GitHub Actions, Terraform, GKE/Kubernetes, GCP
• GitHub, JFrog Artifactory
• MCP protocol, LLM evaluation infrastructure, eval platforms
• Agent orchestration systems, environment provisioning automation
• Multi-agent orchestration, sub-agent frameworks
• Inner-source, AI model tracking, SOX controls

Minimum education and experience

• Minimum of 9 years of solid, diverse work experience in software engineering, with a minimum of 6 years in application development, including significant recent experience (2+ years) building or operating AI-augmented development tools, agentic systems, or developer platforms.
• Hands-on experience with LLM-based engineering tools (Claude Code, Cursor, GitHub Copilot, or equivalent) in production engineering workflows.
• Experience designing and scaling inner-source or platform engineering programs across large engineering organizations is preferred.
• Applicable certifications in cloud platforms (GCP, AWS), AI/ML, or security are preferred.
• Bachelor’s Degree with Master’s preferred in Computer Science, AI/ML, or related discipline, or equivalent work experience.

Reporting relationship

Typically Director or above

Benefits

• CNA offers a comprehensive and competitive benefits package
• cnabenefits.com