DevOps Engineer

• Design, implement, and maintain CI/CD pipelines for applications, APIs, batch jobs, and data pipelines.
• Automate build, test, and deployment processes including artifact and version management.
• Provision and manage cloud infrastructure including compute, networking, and storage resources.
• Implement Infrastructure as Code using tools such as Terraform and manage environment promotion strategies.
• Build and optimize containerized applications using Docker and managed container platforms.
• Implement orchestration, autoscaling, and resiliency strategies.
• Establish monitoring, logging, and tracing for applications, models, and data pipelines.
• Perform troubleshooting, error analysis, and performance optimization.
• Integrate security practices into CI/CD pipelines including scanning, secrets management, and access controls.
• Collaborate with data scientists and engineering teams to streamline development and deployment processes.
• Develop documentation, runbooks, and reusable templates to support DevOps practices.

Requirement/Must Have:

• 3 5+ years of experience in DevOps or platform engineering.
• Strong experience with CI/CD tools and pipeline development.
• Proficiency in cloud platforms including Azure and AWS.
• Hands-on experience with Infrastructure as Code, primarily Terraform.
• Experience with containerization using Docker and orchestration platforms such as Kubernetes.
• Strong scripting and automation skills.
• Experience with monitoring and observability tools.
• Knowledge of security best practices in DevOps environments.
• Strong communication and collaboration skills.

Experience:

• Experience managing Windows servers and familiarity with Linux systems.
• Experience implementing monitoring, logging, and alerting solutions.
• Experience with cloud infrastructure design and cost optimization.
• Experience working in Agile environments.

Responsibilities:

• Build and maintain scalable DevOps pipelines and infrastructure.
• Ensure system reliability, performance, and security.
• Collaborate with cross-functional teams to deliver efficient solutions.
• Support deployment and operational processes.
• Maintain documentation and best practices.

Should Have:

• Experience supporting AI or machine learning workloads.
• Familiarity with ML tools and data engineering workflows.
• Experience with GPU-based deployments and optimization.
• Experience in enterprise or regulated environments.

Skills:

• Strong automation and scripting abilities.
• Expertise in CI/CD pipeline development.
• Cloud infrastructure and architecture knowledge.
• Problem-solving and analytical skills.
• Effective communication and teamwork.

Qualification And Education:

• Bachelor s degree in Computer Science, Information Technology, or related field preferred.