Principal AI Engineer

You have a clear vision of where your career can go. And we have the leadership to help you get there.At CNA we strive to create a culture in which people know they matter and are part of something important ensuring the abilities of all employees are used to their fullest potential.

JOB DESCRIPTION:

Essential Duties & Responsibilities
Performs a combination of duties in accordance with departmental guidelines:

• Acts as one of principal engineers for CNAs AI-native engineering platform designing the end-to-end system spanning agentic coding workflows skills and agent marketplaces AI-augmented CI/CD pipelines automated quality gates and rapid environment provisioning. Leads integration of AI tooling (Claude Code Cursor GitHub Copilot) into the software delivery lifecycle ensuring these capabilities compose into a coherent governed platform.

• Designs and builds the agentic infrastructure layer including multi-agent orchestration patterns sub-agent frameworks skill authoring standards and context engineering best practices that enables engineering teams to operate at AI-native speed without sacrificing architectural integrity or security posture.

• Provides expert technical consultation to engineering leadership portfolio teams and architecture on how to adopt AI-native development practices evaluate AI-generated code quality and integrate agentic tooling into existing workflows. Advises on trade-offs between speed and quality human-in-the-loop requirements and appropriate levels of AI autonomy for different risk profiles (e.g. Sox-classified systems vs. rapid prototyping).

• Leads the technical strategy for the centralized skills and agent marketplace defining contribution standards review processes and governance models that enable inner-source contribution at scale while maintaining enterprise quality and security requirements. Establishes what qualifies as a skill an agent and an MCP configuration at the enterprise level.

• Acts as the senior technical resource mentoring engineers across the organization in AI-native engineering practices including agentic coding patterns context engineering prompt-to-code workflows and AI-assisted testing raising the floor of capability so teams become self-sustaining without ongoing coaching dependency.

• Researches evaluates and recommends AI engineering tools frameworks and infrastructure (e.g. eval platforms agent orchestration systems environment provisioning automation) aligned with CNAs strategic direction. Leads build-vs-buy analysis for platform capabilities such as CI/CD tooling sandbox provisioning and LLM evaluation infrastructure.

• Partners closely with Architecture Security Cloud Engineering and Data teams to ensure the AI engineering platform integrates with enterprise infrastructure (GCP/GKE GitHub JFrog Artifactory) meets regulatory and compliance requirements (AI model tracking Sox controls) and scales to support hundreds of engineers and AI pod teams across all portfolios.

Reporting Relationship
Typically Director or above

Skills Knowledge & Abilities

• 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 with specific expertise in 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 in building and operating CI/CD platforms (GitHub Actions or equivalent) infrastructure-as-code (Terraform) container orchestration (GKE/Kubernetes) and cloud platforms (GCP) with the ability to design pipelines that enforce quality and security gates without creating delivery bottlenecks.

• Strong knowledge of application security engineering including supply chain security artifact management and curation static/dynamic analysis secret management and the specific attack vectors introduced by AI-generated code (dependency hallucination model drift prompt injection).

• Demonstrated ability to design developer platforms and tooling that serve hundreds of engineers at varying skill levels balancing power-user capability with guardrails that prevent misuse and maintain code quality at scale.

• Proven ability to evaluate and integrate emerging AI technologies rapidly with the judgment to distinguish between hype and production-ready capability. Comfortable operating in a fast-moving domain where the tooling landscape changes weekly.

• Excellent communication skills with the ability to translate complex AI engineering concepts for both technical and non-technical audiences. Able to influence engineering culture and drive adoption of new practices across a large diverse organization 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 rather than tooling adoption metrics.

Education & Experience

• Bachelors Degree with Masters preferred in Computer Science AI/ML or related discipline or equivalent work 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.

• Demonstrated hands-on experience with LLM-based engineering tools (Claude Code Cursor GitHub Copilot or equivalent) in production engineering workflows not just experimental use.

• Experience designing and scaling inner-source or platform engineering programs across large engineering organizations preferred.

• Applicable certifications in cloud platforms (GCP AWS) AI/ML or security preferred.

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In certain jurisdictions CNA is legally required to include a reasonable estimate of the compensation for this District of Columbia California Colorado Connecticut Illinois Maryland Massachusetts New York and Washington the national base pay range for this job level is $97000 to $189000 determinations are based on various factors including but not limited to relevant work experience skills certifications and location. 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. For a detailed look at CNAs benefits please visit.

CNA is committed to providing reasonable accommodations to qualified individuals with disabilities in the recruitment process. To request an accommodation please contact.