Senior Azure DevOps Engineer

Scrums.com, Inc.; United States; Remote; USD 83,000 - 165,000; Part time

Job summary

Scrums.com, Inc. seeks a Senior Azure DevOps / Platform Engineer to own the cloud platform powering high-scale systems. This flexible 80-hour-per-period contract lets you shape provisioning, security, and observability with autonomy.

You’ll work across Azure, Kubernetes-adjacent tooling, data infrastructure, and AI/GPU workloads while crafting repeatable, isolated customer environments at scale.

Qualifications

• Proven senior-level Azure in production
• Terraform and/or Bicep for IaC
• CI/CD with Azure DevOps and/or GitHub Actions
• Automate repeatable, isolated customer environments
• Azure identity, RBAC, Key Vault skills
• Private networking (VNets, endpoints)
• Monitoring, logging, distributed tracing
• Backup/DR planning and security hardening
• Cost management at scale

Responsibilities

• Design, build, and maintain IaC with Terraform/Bicep across Azure environments
• Manage CI/CD pipelines with Azure DevOps and/or GitHub Actions
• Automate environment provisioning and container deployment for isolated customer environments
• Configure Azure identity, RBAC, and Key Vault secrets management
• Implement private networking architectures (VNets, endpoints)
• Set up monitoring, logging, and tracing across environments
• Own backup and DR processes and security hardening
• Monitor cloud costs and identify optimization opportunities
• Deploy and operate MongoDB/Atlas and Kafka infrastructure
• Support AI/model-serving infra, including GPU provisioning

Skills

Azure

Terraform

Bicep

Azure DevOps

GitHub Actions

RBAC

Key Vault

VNet

Private Endpoints

Monitoring/Tracing

Cost optimization

GPU compute

Tools

MongoDB Atlas

Kafka

Kubernetes tooling

Job description

Join Scrums.com as a Senior Azure DevOps / Platform Engineer and take ownership of the cloud platform powering mission-critical, high-scale systems, on a flexible 80 hour basis that fits around other commitments.This is a chance to work at the infrastructure core of modern, AI-enabled platforms: building the automation, security, and observability that let engineering teams ship fast and safely.You'll have real autonomy to design and evolve environment provisioning practices from the ground up, with your work directly shaping how repeatable, isolated customer environments are automated at scale.A strong fit for a hands-on platform engineer who wants meaningful technical ownership without a full-time commitment, working across Azure, Kubernetes-adjacent container tooling, data infrastructure, and emerging AI/GPU workloads.

Responsibilities

• Design, build, and maintain infrastructure as code using Terraform and/or Bicep across Microsoft Azure environments.
• Manage CI/CD pipelines using Azure DevOps and/or GitHub Actions.
• Automate environment provisioning and container deployment, with particular emphasis on repeatable, isolated customer environments.
• Configure and maintain Azure identity and RBAC, including Key Vault and secrets management.
• Implement private networking architecture, including VNets and private endpoints.
• Set up and maintain monitoring, logging, and distributed tracing across environments.
• Own backup and disaster recovery processes, and apply production security hardening best practices.
• Monitor and manage cloud cost, identifying and implementing optimisation opportunities.
• Deploy and operate MongoDB/Atlas and Kafka infrastructure.
• Support AI/model-serving infrastructure, including GPU compute provisioning where applicable.

Experience and education

• Proven senior-level experience with Microsoft Azure in production environments.
• Strong hands-on experience with Terraform and/or Bicep for infrastructure as code.
• Practical experience with Azure DevOps and/or GitHub Actions for CI/CD.
• Demonstrated experience automating repeatable, isolated customer environments, this is a priority requirement for the role.
• Solid understanding of Azure identity, RBAC, and secrets management (Key Vault).
• Experience with private networking, VNets, and private endpoints.
• Experience implementing monitoring, logging, and distributed tracing solutions.
• Experience with backup/disaster recovery planning and production security hardening.
• Experience managing cloud cost at scale.
• Experience deploying and operating MongoDB/Atlas and Kafka infrastructure.
• Exposure to AI/model-serving infrastructure and GPU compute is an advantage.