Senior Software Engineer - Cloud Development

Job description

• Design, implement, and maintain DevOps continuous Integration (CI) continuous delivery (CD) pipelines to manage from code build to deployment and cloud infrastructure using Infrastructure as code practices to meet business needs.
• Have a deep understanding of modern DevOps development tools and practices involved with Continuous Integration, Continuous Deployment, Continuous Testing/Security and Continuous Monitoring/Observability.
• Guide the junior DevOps Engineers to build /enable DevOps capabilities and practices. In addition, the individual should be able to work with the Application Delivery directors to ensure there is alignment of DevOps strategy to application delivery.
• Mentor the junior members through practices and tools enablement, including a focus on automation and defining new ways of working, along with a modern development toolset.
• Committed to continuous improvement: Dedicated to adopting cutting-edge technologies like AI/ML to optimize DevOps processes.

About You:

• 7+ years of relevant work experience in DevOps.
• Should have hands on and good understanding of DevOps tools and automation frameworks.
• Expertise in python scripting (must have)
• Demonstrated hands-on experience with DevOps techniques building continuous integration and continuous delivery solutions using Jenkins, Docker, GitHub, GitHub Actions.
• Experience in configuration management tools Experience with implementation of Infrastructure as code (Terraform, CloudFormation).
• Experience with monitoring tools like Datadog, Splunk or any other monitoring tools/processes.
• Experience working in Agile environments.
• Ability to handle multiple competing priorities in a fast-paced environment.
• Problem-solving skills and ability to follow through to completion.
• Experience in coaching junior members in the team remove roadblocks and solve large scale problems including working with teams across all business segments.
• Have a creative ability to identify key metrics and measure results to track the DevOps transformation progress.
• Experience in using AI/ML as a part of DevOps practice. (Good to have)