A fast-growing AI and cloud company seeks a senior engineer to lead Azure infrastructure design, automation, and reliability. The role involves building scalable, secure environments and implementing CI/CD and MLOps pipelines. It offers a high-impact opportunity to shape the future of AI applications with modern cloud and automation technologies.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
Senior Cloud & DevOps Engineer – Azure & MLOps
Location: Hybrid (U.S.)
Compensation: $140,000 – $160,000 base + equity and relocation
About the Company
A fast-growing AI and cloud technology company is building secure, scalable, and intelligent applications that leverage Microsoft Azure and machine learning.
The organization is reimagining how cloud-native infrastructure supports real-time AI systems—empowering product and data teams to innovate quickly while maintaining enterprise-grade reliability, performance, and security.
They are investing heavily in modern Azure infrastructure and automation to enable faster development cycles, deeper observability, and robust MLOps capabilities.
The Role
The Senior Cloud & DevOps Engineer (Azure & MLOps) will own the design, automation, and reliability of the company’s Azure cloud ecosystem.
You’ll be responsible for architecting secure, high-availability environments; implementing end-to-end CI/CD and MLOps pipelines; and optimizing the infrastructure powering next-generation AI applications.
This is a hands-on, high-impact role for an engineer who thrives at the intersection of cloud systems, automation, and applied machine learning.
Key Responsibilities
- Design & Manage Azure Infrastructure: Build and manage environments using Infrastructure as Code (Bicep or Terraform) across App Services, Static Web Apps, Cosmos DB, and Azure SQL.
- Automate CI/CD & MLOps Pipelines: Develop and maintain build, test, and deployment pipelines in Azure DevOps or GitHub Actions for web and ML workloads.
- Implement Observability & Monitoring: Use Azure Monitor and Application Insights to ensure high performance, uptime, and model visibility.
- Champion Cloud Security: Apply Azure security best practices across networking (VNETs, NSGs), IAM, and data encryption.
- Optimize for Scale & Cost: Monitor usage and design scalable, cost-efficient systems.
- Enable Machine Learning Operations: Integrate and manage ML deployment workflows to support continuous model delivery and monitoring.
About You
- 5+ years of experience in Cloud or DevOps Engineering, with deep knowledge of Microsoft Azure.
- Strong expertise in CI/CD pipelines (Azure DevOps or GitHub Actions) and Infrastructure as Code (Bicep or Terraform).
- Hands-on experience with Docker and automation scripting (PowerShell or Bash).
- Skilled in cloud security, networking, and observability.
- Experience or interest in AI/ML system deployment and MLOps frameworks.
- Bachelor’s degree in Computer Science or a related field, or equivalent professional experience.
Bonus Points:
- Azure certifications (e.g., AZ-400, AI-102)
- Experience with Kubernetes / Azure Kubernetes Service (AKS)
- Familiarity with Azure ML, MLflow, or similar MLOps tools
- Understanding of compliance frameworks such as HIPAA or SOC 2
Tech Stack
Azure, Bicep/Terraform, Azure DevOps, GitHub Actions, Docker, PowerShell, Bash, Cosmos DB, Azure SQL, Redis, Application Insights, Azure Monitor, Azure ML, AKS
Why Join
- Competitive compensation: $140K–160K base + equity + relocation
- Hybrid work flexibility across the U.S.
- Comprehensive health, dental, and vision coverage
- Opportunity to define the DevOps and MLOps foundation for a cutting-edge AI platform
- Collaborative, forward-thinking engineering culture with real ownership and impact