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CNA

Senior AI Software Engineer

Chicago, IL, USA

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hirly's read of this role

Role family
Engineering
Seniority
Senior
Country
US
Work mode
On-site / unstated
First seen by hirly
22 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

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.

Senior individual contributor on the Developer Experience (DevX) platform team, responsible for designing, building, and operating an AI-native software delivery platform across five capability domains: FeedBack (AI intelligence, observability, DORA metrics), Enterprise Enablement (Internal Developer Portal, golden-path onboarding), Build & Delivery (CI/CD/CT, GitHub Actions, ArgoCD, Harness), Safety / Application Security (Veracode, SonarCloud, JFrog Xray, supply-chain security), and App Accelerator (container base images, dev containers, starter app templates). Leads the development of AI agentic SDLC workflows — autonomous and human-in-the-loop agents that accelerate code generation, PR review, test authoring, vulnerability remediation, and deployment across engineering teams — in direct support of the platform's north-star goal of taking a developer from template selection to a running pre-production application in 10 minutes or less. Acts as a force multiplier for DevX, partnering with platform, security, container, and product engineering to embed AI assistance into every stage of the SDLC.

JOB DESCRIPTION:

Essential Duties & Responsibilities

Performs a combination of duties in accordance with departmental guidelines:

Own and evolve the Internal Developer Platform (Harness IDP) — self-service catalog, scaffolding templates, and golden-path workflows targeting the platform's north-star goal: developer selects a template and has an application deployed to pre-production in 10 minutes or less.

Architect and own CI/CD/CT pipelines on GitHub Actions, ArgoCD , and Harness across the Build & Delivery domain ; design for reliability, security, and progressive delivery — able to design and operate end-to-end, not just configure.

Design and build AI agentic SDLC workflows: event-driven agents that autonomously perform code generation, PR review, test authoring, Veracode vulnerability auto-remediation, SonarCloud gate enforcement, and release orchestration across the delivery pipeline.

Implement evaluation frameworks for agentic systems ( Arize , Phoenix, or equivalent) — define ground truth datasets, regression suites, guardrails, and online/offline evals to ensure AI agents operating inside the SDLC remain safe, accurate , and auditable.

Drive supply-chain security inside the Application Security domain: integrate SBOM generation ( JFrog Xray, Syft , or Anchore ) into delivery pipelines, contribute to the Binary Authorization and container image hardening initiative for Kubernetes workloads, and design automated policy gates and remediation flows.

Contribute to the App Accelerator domain — maintain and evolve container base images, dev container definitions, and starter app templates so that golden-path scaffolded applications are current, secure, and ready for AI-assisted development from day one.

Operate feature flag and progressive-delivery platforms ( LaunchDarkly , Unleash, GCP-native, or equivalent); design kill-switches, canary patterns, and safe rollout strategies that protect production while enabling continuous delivery.

Embed observability (Datadog, Dynatrace, Elastic, or equivalent) into platform services and delivery pipelines across the FeedBack domain; own DORA metric instrumentation (deployment frequency, lead time, change failure rate, MTTR) and Application Health dashboards used to measure engineering performance.

Champion adoption of AI coding assistants (Claude Code, Cursor, GitHub Copilot) in an AI-native SDLC; build the guardrails, prompt patterns, and developer workflows that make AI-assisted development repeatable and safe at enterprise scale; contribute to the Code Quality as a Service offering alongside Veracode and SonarCloud .

Mentor engineers across the DevX and App Accelerator teams; act as a technical consultant for platform adoption, agentic AI patterns, and delivery best practices.

Partner with security, infrastructure, architecture, and product engineering counterparts on platform direction, roadmap, and architectural standards; represent DevX in cross-team initiatives spanning container governance, GitHub security controls, and CI/CD policy.

May perform additional duties as assigned.

Reporting Relationship

Typically Director or above

Skills, Knowledge & Abilities

Required

7+ years in platform engineering with deep CI/CD pipeline ownership in a regulated, enterprise-scale environment (insurance, financial services, or equivalent).

Hands-on with GitHub Actions, ArgoCD , Harness, or comparable CD platforms — able to design and operate end-to-end, not just configure.

Proficient using AI coding tools (Claude Code, Cursor, GitHub Copilot, or equivalent) in an AI-native SDLC workflow; experience building guardrails and adoption patterns for these tools at team or enterprise scale.

Direct experience building or operating an Internal Developer Platform (Harness IDP, Backstage, Port) with a self-service catalog, golden-path scaffolding, and measurable time-to-value metrics (e.g., time to first deployment).

Feature flags and progressive-delivery experience ( LaunchDarkly , Unleash, GCP-native, or equivalent) including kill-switch design and canary rollout patterns.

SBOM and supply-chain integration experience ( JFrog Xray, Syft , Anchore ) inside a delivery pipeline, including Binary Authorization or equivalent container image hardening and policy-gate design.

Hands-on with observability platforms (Datadog, Dynatrace, Elastic, or equivalent); able to instrument DORA metrics, define SLOs, and build actionable engineering-performance dashboards.

Familiarity with SAST/DAST tooling (Veracode, SonarCloud , or equivalent) in an enterprise pipeline context — ideally including automated triage or remediation workflows.

Experience designing and building event-driven AI agents that autonomously complete SDLC tasks, and building evals for agentic systems using Arize , Phoenix, or equivalent.

Strong analytical and problem-solving skills; excellent communication and interpersonal skills; able to work effectively with engineers, IT leadership, security, and business stakeholders.

Demonstrated ability to lead platform initiatives, drive cross-team adoption, and mentor engineers.

Preferred

Insurance or financial-services industry background; familiarity with regulatory and compliance requirements for software delivery.

Experience with security-as-code, OPA/Rego policy authoring, or compliance-automation pipelines (e.g., GitHub governance at scale, branch protection policy-as-code).

Hands-on with container base image pipelines, dev container standards, or starter app template frameworks.

Open-source contributions to platform engineering, developer tooling, or AI-agent projects.

​

Education & Experience

Bachelor's degree in Computer Science or related discipline, or equivalent work experience.

Minimum of 7 years of platform and software engineering experience, including direct ownership of enterprise CI/CD pipelines in a regulated industry.

Previous technical leadership experience on platform, developer-tooling, or AI-engineering initiatives.

Applicable certifications preferred (e.g., GitHub Actions, Kubernetes, cloud provider, or Harness certifications).

#LI-KJ1 #LI-HYBRID

I n 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 $72,000 to $141,000 annually. Salary determinations are based on various factors, including but

Original posting on CNA's site ↗

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