Software Engineering Manager- Build and Release Engineering
Hewlett Packard Enterprise (HPE) (company site, opens in a new tab)15–20 yrsBengaluruOn-siteDirect career pageEst. 45–70 LPA
Posted on 23 Sept
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Job description
Structured overview of role & requirements
About This Role
- Lead and manage a high-performing engineering team responsible for build, release engineering, source code administration, and sandbox tooling for large-scale systems such as HPE Networking's JUNOS and EVO platforms.
- Own and drive the architecture, scalability, reliability, and DevSecOps strategy of enterprise-wide CI/CD infrastructure, source code management, and sandbox platforms, directly contributing to code and complex technical decisions.
- Establish best practices, lead incident management and root cause analysis, and promote adoption of AI/ML-driven automation and observability to improve delivery pipelines and security.
Minimum Requirements
- Bachelor's or master's degree in computer science, electrical engineering, or related field.
- 15-20 years of experience in build/release engineering, source code administration, or infrastructure engineering with progressive leadership responsibility.
- At least 5 years managing engineering teams while staying technically engaged in coding, design reviews, and production troubleshooting.
- Experience with large-scale CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions), source control systems (Gerrit, SVN, GitLab, GitHub), SBOM and VEX management, and strong programming/scripting skills (Python, Bash, Go, etc.).
- Role location is onsite at HPE office (explicitly mentioned).
Ideal Candidate Profile
- Hands-on engineering manager who balances people leadership with direct technical contributions and troubleshooting at scale.
- Extensive experience architecting and operating complex, multi-repository CI/CD and source code management platforms in enterprise environments.
- Demonstrated ability to lead cross-functional DevSecOps initiatives and drive adoption of emerging technologies such as AI/ML for automation and observability.