Principal AI Engineer

01460 Continental Casualty Company; Chicago (IL); Hybrid; USD 97,000 - 189,000; Full time

Job summary

CNA in Chicago, IL is seeking a senior engineer to lead the AI-native engineering platform, designing end-to-end systems for agentic coding workflows, AI tooling integration, and scalable infrastructure.

You will mentor engineers, establish architectural standards, and collaborate with security and cloud teams to scale the platform; drive data-driven decisions while aligning with regulatory requirements. This role supports innovation across portfolios and operates within a hybrid work model.

Qualifications

• Bachelor's Degree and Master’s preferred in Computer Science, AI/ML, or related field; 9+ years in software engineering; recent AI-augmented development tools experience.

Responsibilities

• Design end-to-end AI-native platform systems.
• Lead integration of AI tooling into SDLC.
• Mentor engineers in AI-native practices.
• Advise on speed vs. quality trade-offs and AI autonomy levels.
• Collaborate with Architecture, Security, Cloud, and Data teams.

Skills

AI-native engineering

Agentic coding workflows

Prompt engineering

Context engineering

Multi-agent orchestration

CI/CD pipelines

Security posture

Education

Bachelor's Degree; Master's preferred in CS/AI

Tools

GCP

GKE

GitHub

JFrog Artifactory

Job description

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.

Essential Duties & Responsibilities

Performs a combination of duties in accordance with departmental guidelines:

• Acts as one of principal engineers for CNA's 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 and implementation for engineering metrics platform.
• Consult with senior tech leadership stakeholders to provide insights in data-driven decision making.
• 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 CNA's 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.
• May perform additional duties as assigned.

Reporting Relationship Typically Director or above.

Skills, Knowledge & Abilities

• Expert knowledge in 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.
• Proficient 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

Bachelor's Degree with Master's 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 in 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.

Compensation & Benefits

In certain jurisdictions, CNA is legally required to include a reasonable estimate of the compensation for this role. In District of Columbia, California, Colorado, Connecticut, Illinois, Maryland, Massachusetts, New York and Washington, the national base pay range for this job level is $97,000 to $189,000 annually. Salary 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 CNA’s benefits, please visit cnabenefits.com.

Recruiting & Accessibility

CNA utilizes AI-enabled technology during the recruiting process. For more information, please visit our careers page. CNA is committed to providing reasonable accommodations to qualified individuals with disabilities in the recruitment process. To request an accommodation, please contact [e-mail].

Corporate Culture & Values

At CNA, we are focused on success, individually and collectively. We pride ourselves on promoting a culture that challenges and engages people. We strive to connect people, departments and business areas, to function as a team, and to serve our customers and communities with professionalism and respect. Our dedication to employee engagement, continuous learning and the open exchange of ideas is the cornerstone of our business. These ideals, combined with our focus on the customer, enable us to explore new market opportunities and build on our success. Our values, culture and financial strength are what differentiates us from other employers and make CNA the place you want to work. At CNA, we are committed to advancing a culture of inclusion – one that attracts talent from all walks of life, fosters respect and collaboration, and enables all of our colleagues to do their best work. At CNA, we have a long standing commitment to the diverse communities in which we live and work. We actively make a difference for the greater good through partnerships, sustainability, initiatives, and working together for a better tomorrow. Corporate Social Responsibility is not one person, or one department, it's the entire enterprise coming together to make the world a better place.

Legal & Compliance

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