Job description

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Developer, DevOps Engineer

Intended for use by Business Leaders and Managers. Please work with your HR Business Partner to complete each section.

Position Title:

DevOps Engineer

Job Family:

IT & Digital

Job Summary:

The DevOps Engineer designs, builds, automates, and operates secure, scalable, and reliable cloud platforms and delivery capabilities. The role supports AWS and GCP environments, with working awareness of Azure, and uses Git and GitHub, Terraform, Linux, Python or PowerShell, and CI/CD practices to standardize infrastructure, accelerate software delivery, and improve operational performance. Working across internal developer platforms, cloud foundations, automation, observability, networking, FinOps, and AI-assisted engineering, the position enables product teams to deliver efficiently while meeting architecture, security, resilience, cost, and compliance standards.

Job Responsibilities:

Design, build, configure, and operate secure cloud foundations and shared platform services across AWS and GCP, with awareness of Azure services and integration patterns.
Develop and maintain infrastructure automation using Terraform and related infrastructure-as-code practices, ensuring repeatable provisioning, configuration consistency, and controlled change.
Create, improve, and support CI/CD pipelines using Git and GitHub-based workflows, automated quality gates, security checks, artifact management, and reliable deployment patterns.
Contribute to the Internal Developer Platform by delivering reusable templates, self-service capabilities, paved-road patterns, documentation, and developer enablement tools.
Automate operational and engineering tasks using Python or PowerShell and apply strong Linux fundamentals to administration, scripting, troubleshooting, and platform support.
Implement monitoring, logging, tracing, alerting, dashboards, and service health practices that strengthen observability, availability, performance, and operational readiness.
Apply basic networking concepts—including DNS, routing, firewalls, load balancing, connectivity, and certificates—to diagnose and resolve cloud and delivery issues.
Partner with software engineers, architects, cybersecurity, operations, and product teams to improve delivery flow, platform adoption, reliability, and incident resolution.
Embed FinOps practices through tagging, cost visibility, usage optimization, rightsizing, and actionable recommendations that balance performance, resilience, and cloud spend.
Use approved AI-assisted engineering tools responsibly to accelerate scripting, troubleshooting, testing, documentation, and automation while validating outputs and protecting company data and intellectual property.

Competencies:

DevOps and platform engineering mindset focused on automation, self-service, standardization, reliability, security, and developer experience.
Hands-on analytical problem solving across Linux, cloud services, CI/CD pipelines, source control, infrastructure automation, monitoring, and networking.
Working knowledge of AWS and GCP cloud foundations, with transferable understanding of Azure and multi-cloud operating principles.
Ability to write maintainable automation in Python or PowerShell and collaborate effectively through Git and GitHub workflows.
Understanding of observability, secure engineering, operational resilience, incident management, and continuous improvement.
Collaboration, communication, ownership, and customer focus in a global, cross-functional, and multicultural environment.
Practical awareness of FinOps and AI-assisted engineering, including cost-conscious design, output validation, prompt discipline, privacy, security, and ethical use.

Key Performance Indicators:

Reliability, availability, performance, and security of supported cloud foundations, platform services, and delivery pipelines.
Lead time, deployment frequency, change success rate, and recovery performance improved through effective CI/CD and automation.
Adoption and reuse of Internal Developer Platform capabilities, templates, standards, and self-service workflows.
Quality, maintainability, documentation, and policy compliance of infrastructure automation, scripts, GitHub workflows, and platform components.
Reduction in recurring incidents, manual effort, alert noise, and time to detect and resolve operational issues.
Cloud cost visibility and optimization outcomes achieved through tagging, usage analysis, rightsizing, and FinOps recommendations.
Appropriate use of approved AI-assisted engineering tools to improve productivity without compromising quality, security, or compliance.

Minimum Qualifications (if applicable include physical requirements to comply with ADA):

Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related field, or an equivalent combination of education and relevant experience.
Typically 2–4 years of relevant experience in DevOps, cloud engineering, platform engineering, site reliability engineering, or infrastructure automation.
Hands-on experience with AWS or GCP and foundational knowledge of the other major cloud platforms, including Azure.
Working knowledge of Git and GitHub, CI/CD concepts, automated delivery workflows, and infrastructure discovery or automation using Terraform or comparable tooling.
Strong Linux fundamentals and practical scripting experience with Python or PowerShell.
Understanding of monitoring and observability concepts, including metrics, logs, traces, alerting, dashboards, and service health.
Foundational networking knowledge covering IP addressing, DNS, routing, firewalls, load balancing, connectivity, and TLS certificates.
Exposure to Internal Developer Platforms, cloud foundations, automation, FinOps, operational support, and secure engineering practices.
Foundational knowledge of AI-assisted engineering tools and the ability to use them responsibly for automation, analysis, troubleshooting, testing, and documentation.
Ability to communicate effectively in English and work in a global, distributed team environment.

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