Senior AI Software Engineer

• 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; designfor reliability, security, and progressive delivery — able to design andoperateend-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,SonarCloudgate 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 agentsoperatinginside the SDLC remain safe,accurate, and auditable.

• Drive supply-chain security inside the Application Security domain: integrate SBOM generation (JFrogXray,Syft, orAnchore) 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 —maintainand 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 theFeedBackdomain; 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 andSonarCloud.

• Mentor engineers across theDevXand App Acceleratorteams;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; representDevXin cross-team initiatives spanning container governance, GitHub security controls, and CI/CD policy.

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 andoperateend-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 atteamor enterprise scale.

• Direct experience building oroperatingan 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 (JFrogXray,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 usingArize, 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 orfinancial-servicesindustry 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.