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Metro location and generalist DevOps role with broad toolset increase applicant competition.
Fundamental DevOps and cloud skills transfer across industries, though AI-PDLC and MCP raise domain specificity.
Explicit 1–3 years and many mandatory cloud, IaC, scripting, and AI-tooling skills increase shortlisting strictness.
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Design, automate, and deploy core SDLC productivity tools collaborating with software engineering teams.
Maintain and optimize cloud-native toolchains to enable AI-product development lifecycle with zero operational gaps.
Track, report, and visualize engineering performance metrics globally using DORA and SPACE frameworks.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
1 to 3 years of experience in cloud environments and scalable SaaS architectures.
Proficiency in scripting languages (Python, TypeScript, or Go) and Infrastructure as Code (Terraform/CloudFormation).
Practical operational knowledge of AWS primarily, with exposure to Azure or GCP.
Experience working in or supporting global, distributed engineering teams across multiple countries and time zones.
Background integrating AI-assisted development tools (e.g., GitHub Copilot) within software development environments.
Strong analytical skillset to extract and act on engineering workflow data and metrics to improve processes.