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Popular mid-level DevOps role in metro with broad toolset and 1–3 years experience attracts many applicants.
Core DevOps skills are transferable, but AI-PDLC and MCP requirements raise domain specificity.
Explicit years plus mandatory cloud, IaC, scripting, and AI-tooling requirements increase filtering rigor.
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Lead automation and deployment of productivity tools to optimize the software development lifecycle across Trimble's global engineering teams.
Operate and govern cloud-native AI-product development lifecycle (AI-PDLC) toolchains ensuring continuous operational readiness without gaps.
Develop and maintain engineering performance metrics dashboards and intelligent support workflows with AI integration for over 11,000 global users.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related technology discipline.
1 to 3 years of experience with cloud environments and scalable SaaS architectures.
Proficiency in scripting (Python, TypeScript, or Go), Infrastructure as Code (Terraform/CloudFormation), and containerization tools.
Practical operational knowledge of AWS with exposure to Azure or GCP; experience integrating AI engineering tools (e.g. GitHub Copilot, Atlassian Rovo).
Experienced working in a hybrid role requiring collaboration across multiple global business units and engineering teams in a matrix environment.
Skilled in data-driven operational insights using engineering metrics frameworks such as DORA and SPACE for process improvement.
Comfortable managing and securing AI-driven software development workflows interfacing with cybersecurity tools and policies.