Job Description

About the Team:
Join a high-performing Data Engineering and AI team working closely with Data Scientists and AI Engineers to deliver cutting-edge solutions on Azure. Our primary product is hosted on Azure Kubernetes Service (AKS), with daily releases of backend services, APIs, and UI components. We are scaling our DevOps capabilities to support secure, observable, and intelligent deployments.
Key Responsibilities:
CI/CD & DevSecOps:

• Design, build, and maintain robust CI/CD pipelines using Azure DevOps for data engineering and AI projects

• Integrate DevSecOps tools such as Snyk Code and Snyk Container for static code analysis and container vulnerability scanning.

• Automate security gates and compliance checks in the deployment lifecycle.

Azure Kubernetes & Deployment Management:

• Manage and optimize AKS clusters, including scaling, upgrades, and network policies.

• Collaborate with developers to containerize applications

• Improve performance and scalability of the cluster

Monitoring & Observability:

• Set up and maintain observability tools like Azure Monitor, Application Insights, Prometheus/Grafana, or Open Telemetry.

• Define SLIs/SLOs and alerting strategies for proactive issue detection.

AI Testing & Integration:

• Work with AI engineers to integrate automated testing for ML models and APIs into the CI/CD pipeline.

• Support model versioning, deployment, and rollback strategies using Azure ML and AKS.

Collaboration & Architecture Support:

• Partner with architects and engineers to design scalable, secure, and cost-effective infrastructure.

• Contribute to infrastructure-as-code (IaC) using Bicep, Terraform, or ARM templates.

Required Experience & Skills:

• 3-5 years of experience in DevOps or Site Reliability Engineering roles.

• Strong hands-on experience with Azure DevOps Pipelines, Azure Kubernetes Service (AKS), Docker & Helm, Azure Key Vault, ACR, and Networking.

• Experience integrating DevSecOps tools (e.g., Snyk, Aqua, Trivy).

• Familiarity with monitoring and logging tools in Azure and open-source ecosystems.

• Exposure to AI/ML workflows and Azure ML is a strong plus.

• Proficient in scripting (Bash, PowerShell, or Python) and Git-based workflows.

• Strong understanding of software development lifecycle (SDLC) and agile practices.

Nice to Have:

• Knowledge of zero-trust security, RBAC, and network policies in Kubernetes.

• Familiarity with AI testing frameworks or ML model CI/CD.

Why Join Us?

• Work on impactful AI and data-driven products in the energy and sustainability domain.

• Collaborate with a passionate team of engineers, scientists, and architects.

• Opportunity to shape the DevOps and MLOps culture from the ground up.

Skills Required