DevOps & Tooling Manager

About the role

The DevOps & Tooling Manager will lead the design, migration, and operation of automation, developer tooling, CI/CD pipelines, and engineering infrastructure for HPE Networking’s global engineering community. This hybrid position requires two days per week on‑site at an HPE office and focuses on moving tooling to a new Puerto Rico environment while building a high‑performing team.

Key responsibilities

• Own the migration of engineering tools, CI/CD pipelines, and workflows to the Puerto Rico environment with zero disruption to releases.
• Hire, mentor, and develop a high‑performing engineering team, setting technical standards and direction.
• Prioritize and manage the developer tooling and infrastructure roadmap, aligning it with global engineering needs.
• Ensure service reliability, manage on‑call rotations, and conduct blameless post‑mortems.
• Drive continuous improvement of CI/CD pipelines, build systems, and artifact management to reduce cycle times.
• Manage containerized platforms and cloud infrastructure using Kubernetes, Terraform, and Ansible, delivering self‑service capabilities.
• Embed security into the release process (SAST, DAST, SBOM, vulnerability management) and promote DevSecOps practices.
• Collaborate with global engineering, release, product, and support teams to define requirements and communicate progress.
• Apply AI/ML models and AI agents to automate workflows and implement AI‑driven operations.

Required profile

• 10+ years of experience in DevOps, SRE, and tooling engineering.
• At least 3 years in a managerial role leading large‑scale release engineering or platform migration initiatives.
• Proven ability to build and scale high‑performing technical teams.

Required skills

• Kubernetes
• Terraform
• Ansible
• CI/CD pipeline design and optimization
• Build systems and artifact management
• Containerization and cloud infrastructure
• DevSecOps (SAST, DAST, SBOM, vulnerability management)
• Site Reliability Engineering (SRE) practices
• AI/ML model integration for automation