Role and responsibilities

- Lead the design, implementation, and optimization of DevOps and DevSecOps practices across application, data, and AI engineering teams.

- Drive AI-PDLC adoption by integrating approved AI tools into CI/CD pipelines, code quality checks, infrastructure automation, release management, and operational workflows.

- Design and manage cloud infrastructure on Microsoft Azure using Infrastructure as Code (Terraform/Bicep).

- Build and maintain automated CI/CD pipelines for application, API, AI/ML, and data platform deployments.

- Implement containerization and orchestration using Docker and Kubernetes (AKS).

- Ensure platform reliability through monitoring, logging, alerting, and automated incident response.

- Integrate security scanning, compliance validation, and policy enforcement into DevSecOps pipelines.

- Collaborate with Architects, Developers, Data Engineers, AI/ML Engineers, QA, Security, and Infrastructure teams.

- Lead production release management, setting management, disaster recovery, and platform optimization.

- Mentor DevOps engineers and drive engineering excellence, automation, and operational maturity.

Required skills

- DevOps & Cloud

- Microsoft Azure

- Azure DevOps

- Azure Kubernetes Service (AKS)

- Azure App Services

- Azure Functions

- Azure Storage





- Azure Key Vault

- Azure Monitor

- Azure Log Analytics

- Azure Application Insights

- CI/CD & Automation

- Azure DevOps Pipelines

- GitHub Actions (Preferred)

- Jenkins (Preferred)

- CI/CD Pipeline Design

- Release Management

- YAML- Pipelines

- Git

- Artifact Management

- Containers & Platform Engineering

- Docker

- Kubernetes

- Helm

- Container Registry (ACR)

- Linux Administration

- Shell Scripting

- PowerShell

- Python (Automation)

- Dev SecOps

- SonarQube

- SAST/DAST Tools

- Dependency Scanning

- Secrets Management

- Security Compliance

- Vulnerability Management

- Policy as Code

Preferred Skills

- 6-12 years of experience in DevOps, Cloud Engineering, or Platform Engineering.

- Minimum 23 years leading DevOps or Platform Engineering teams.

- Strong experience with Microsoft Azure cloud services and Kubernetes.

- Experience implementing DevSecOps and Infrastructure as Code in enterprise environments.

- Experience supporting AI/ML platforms or MLOps is highly desirable.

- Experience working in Pharmaceutical, CRO, Healthcare, or Life Sciences organizations.

- Microsoft Azure Administrator/DevOps Engineer Expert certification preferred.

📌 Azure Devops Engineer (Gurugram)
🏢 Incedo
📍 Gurugram