Lead Release/Software Engineering

Salesforce•Burlington, MA

2d•$172,500 - $260,100•Onsite

About The Position

Salesforce is seeking a Lead Software/Release Engineer to join their Commerce Cloud Engineering team. This role will focus on building tooling, automation, and release infrastructure to integrate AI into the developer workflow. The engineer will write production code, set technical direction, and own systems that enable AI-native development. The impact of this role will be measured by the increased speed, safety, and intelligence with which engineers ship software.

Requirements

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.
A related technical degree required.

Nice To Haves

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).
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.

Responsibilities

Build and operate tooling that integrates AI/LLM capabilities into the software delivery lifecycle, including code generation, automated review, test authoring, and release automation.
Design and automate CI/CD systems incorporating AI-driven quality gates, anomaly detection, and release-risk analysis.
Own release pipelines for a large-scale enterprise platform, covering build, test orchestration, artifact management, deployment, and rollback.
Define processes and guardrails for safe and effective AI adoption across engineering teams, including prompt and tooling standards, evaluation, and rollout.
Instrument the developer workflow and measure AI-adoption impact using data such as 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.
Critically evaluate code (Human or AI-generated) for correctness, quality, security, and performance.
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.