The Experience:

Commerce Cloud Engineering is transforming how we build and ship software by putting AI at the center of the developer workflow. We're hiring a Lead Software/Release Engineer to build the tooling, automation, and release infrastructure that make AI a first-class part of how our engineers code, review, test, and deploy.

This is a hands-on lead role. You'll write production code, set technical direction, and own the systems that move AI-native development from experiment to everyday practice across a large engineering org. Your impact is measured by how much faster, safer, and smarter the engineers around you ship.

What You'll Actually Be Doing:

• Build and operate tooling that integrates AI/LLM capabilities into the software delivery lifecycle - code generation, automated review, test authoring, and release automation.
• Design and automate CI/CD systems that incorporate AI-driven quality gates, anomaly detection, and release-risk analysis.
• Own release pipelines for a large-scale enterprise platform: build, test orchestration, artifact management, deployment, and rollback.
• Define the processes and guardrails for safe, effective AI adoption across engineering teams - from prompt and tooling standards to evaluation and rollout.
• Instrument the developer workflow and measure AI-adoption impact with data: cycle time, quality, throughput, and developer experience.
• Write and review production-grade code (Java, plus pipeline/scripting languages) that other engineers depend on daily.
• Set technical direction and standards; mentor engineers and lead through influence.
• Partner with platform, QE, and product teams to remove friction and accelerate AI-native delivery.

You're Our Person If You Have:

• 8+ years in software engineering, with deep experience in release engineering, build systems, CI/CD, or developer tooling at scale.
• Strong coding ability in Java (or a comparable JVM/strongly-typed language) and experience with build tooling such as Gradle/Maven/Bazel.
• Hands-on expertise with CI/CD platforms (Jenkins, GitLab CI, GitHub Actions, or similar) and pipeline-as-code.
• Practical experience applying AI/LLM tooling to engineering workflows - coding assistants, automated review, agentic tooling, or LLM-backed automation.
• A track record of leading technical initiatives and mentoring engineers without formal authority.
• Experience defining process and measuring outcomes: you turn adoption goals into instrumented, data-driven results.
• A bias toward automation, reliability, and measurable impact.
• Building or evaluating LLM-based developer tools (prompt engineering, eval harnesses, agent frameworks, MCP).
• Cloud infrastructure and containerization (AWS/GCP, Docker, Kubernetes).
• Observability and metrics tooling for build/deploy health and developer productivity (e.g., Splunk, Grafana, ELK stack).
• Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code.
• Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
• Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
• Critically evaluate code (Human or AI-generated) for correctness, quality, security, and performance .
• A related technical degree required.

Even Better If You Have:

• Experience with Salesforce or Commerce Cloud (B2C/ECOM) platforms.
• Experience with other cloud providers (like GCP).
• Contributions to open-source projects.
• Certifications in AWS or related DevOps technologies.

Why This Role?

You'll be at the leading edge of how a major engineering org adopts AI - not as a side project, but as core infrastructure. We value pragmatic automation, data-driven decisions, and a high bar for reliability. If you want leadership and hands-on engineering without the tradeoff, and you want to shape how AI changes the way software gets built, this is it.