Job Title: Deployment Engineer – Azure DevOps & AI Projects

Company: CogniAI Advanced Research Solutions Pvt. Ltd.

Location: Perungudi, Chennai

Employment Type: Full-time | On-site

Experience: 2–5 Years

Work Mode: Work from Office

About the Role

We are looking for a skilled and motivated Deployment Engineer with hands-on experience in Azure DevOps, cloud infrastructure, CI/CD pipelines, and application deployment. The candidate will be responsible for deploying, managing, monitoring, and maintaining AI-driven applications and software solutions in development, staging, and production environments.

The ideal candidate should have strong knowledge of DevOps practices, containerization, automation, and cloud technologies, along with an interest in working on innovative AI and LLM-based projects.

Key Responsibilities1. Azure DevOps & CI/CD

- Design, configure, and maintain CI/CD pipelines using Azure DevOps.
- Automate build, test, and deployment processes for AI and software applications.
- Manage Azure Repositories, Pipelines, and related DevOps services.
- Implement continuous integration and continuous deployment best practices.
- Troubleshoot pipeline failures and resolve deployment-related issues.

2. Application & AI Project Deployment

- Deploy AI/ML applications, APIs, microservices, and web applications across various environments.
- Support deployment of LLM-based applications, AI agents, and other AI-driven solutions.
- Collaborate with AI developers, software engineers, and technical teams to ensure smooth deployment.
- Configure application environments, dependencies, and deployment parameters.
- Ensure reliable and repeatable deployment processes for AI projects.

3. Docker & Kubernetes

- Build, manage, and optimize Docker containers for application deployment.
- Deploy and manage containerized applications using Kubernetes.




- Work with Docker Compose, Kubernetes manifests, and container registries.
- Troubleshoot container-related issues, resource limitations, and deployment failures.
- Support scalable and reliable application deployments.

4. Cloud Infrastructure & Azure Services

- Deploy and manage applications on Microsoft Azure.
- Work with Azure Virtual Machines, Azure Container Registry, App Services, and other relevant Azure services.
- Configure environment variables, secrets, networking, and access permissions.
- Support cloud infrastructure monitoring, maintenance, and optimization.
- Follow security and infrastructure best practices.

5. Monitoring & Troubleshooting

- Monitor application performance, deployment health, and system availability.
- Identify and resolve deployment, infrastructure, and application-related issues.
- Analyze logs and troubleshoot production incidents.
- Collaborate with development teams to resolve technical problems.
- Maintain deployment documentation and operational procedures.

6. Collaboration & Documentation

- Work closely with development, AI engineering, and QA teams.
- Participate in deployment planning, release management, and technical discussions.
- Maintain documentation for CI/CD pipelines, infrastructure configurations, and deployment procedures.
- Follow version control, security, and change management practices.

Required Skills & Qualifications

- Bachelor's degree in Computer Science,



Information Technology, Engineering, or a related field.
- 2–5 years of hands-on experience in DevOps, deployment, or cloud engineering.
- Strong knowledge of Azure DevOps and CI/CD pipelines.
- Practical experience with Docker and containerized applications.
- Working knowledge of Kubernetes and container orchestration.
- Experience with Azure cloud services and deployment environments.
- Good understanding of Linux systems and shell scripting.
- Familiarity with Git and version control systems.
- Experience troubleshooting deployment and infrastructure issues.
- Good communication, problem-solving, and teamwork skills.

Preferred Skills

- Experience deploying AI/ML applications, LLM-based applications, or AI agents.
- Familiarity with Python-based applications and REST APIs.
- Knowledge of Azure Kubernetes Service (AKS).
- Experience with Azure Container Registry (ACR).
- Knowledge of Infrastructure as Code (Terraform or Bicep).
- Familiarity with monitoring tools such as Azure Monitor, Application Insights, or Prometheus/Grafana.
- Understanding of cloud security, networking, and application scalability.
- Experience working with GPU-based AI workloads or model-serving infrastructure.

What We Offer

- Opportunity to work on innovative AI and LLM-based projects.
- Exposure to cloud technologies and modern DevOps practices.
- Collaborative and technically driven work setting.
- Opportunities for professional growth and skill development.

How to Apply

Interested candidates can share their updated resume with the HR team.

Email: [email protected]

Subject: Application for Deployment Engineer – Azure DevOps & AI Projects

Pay: ₹300,000.00 - ₹450,000.00 per year

Benefits:

- Health insurance
- Provident Fund

Work Location: In person

📌 Deployment Engineer – Azure DevOps & AI Projects (Perungudi)
🏢 CogniAI Advanced Research Solutions Private
📍 Perungudi