DevOps Engineer

Job Title : Devops Engineer

Location : Hyderabad

Experience : 3+ years

OSI Digital is looking for a hands-on DevOps Engineer with 3+ years of experience in cloud infrastructure, CI/CD, automation, and observability, who is eager to leverage AI-powered tools and intelligent automation to improve engineering productivity, operational reliability, and incident resolution.

Responsibilities

• Configure, manage, and monitor container orchestration platforms (Docker, Kubernetes).
• Manage source code repositories (Git/GitHub/GitLab/Bitbucket) and branching strategies.
• Implement, manage, and monitor CI/CD pipelines for application and infrastructure deployments.
• Set up and maintain monitoring, alerting, and logging solutions (Prometheus, Grafana, ELK, CloudWatch, etc.).
• Maintain a good understanding of networking concepts.
• Automate repetitive tasks using scripting languages such as Bash, Python, or PowerShell.
• Provision and maintain cloud resources primarily on Azure and manage infrastructure as code (Terraform/ARM).
• Collaborate with development, QA, and support teams to streamline build, deployment, and release processes.
• Troubleshoot and resolve infrastructure, build, and deployment issues in a timely manner.
• Document configurations, procedures, and environments for future reference.

AI-Enabled DevOps and Intelligent Automation

• Leverage AI-powered tools and coding assistants to accelerate infrastructure automation, scripting, troubleshooting, and CI/CD pipeline development.
• Use AI-assisted analysis of application logs, infrastructure metrics, alerts, and deployment failures to identify potential root causes and recommend corrective actions.
• Explore and implement AI-driven automation for incident triage, root cause analysis (RCA), operational reporting, and repetitive operational tasks.
• Integrate AI capabilities with existing DevOps tools and workflows through APIs, webhooks, and automation frameworks.
• Validate AI-generated scripts, configurations, and remediation recommendations for correctness, security, reliability, and operational impact before implementation.
• Follow security best practices when using AI tools, ensuring sensitive information, credentials, and production data are handled appropriately.

Required Skills

• Hands-on experience with CI/CD tools (Jenkins, GitLab CI, Azure DevOps, etc.).
• Experience in at least one scripting language (Bash, Python, or PowerShell).
• Experience with cloud platforms (preferably Azure).
• Good understanding of infrastructure as code (Terraform/CloudFormation/Ansible).
• Good background in Linux/Unix administration.
• Working knowledge of Kubernetes concepts.
• Familiarity with source code management and version control systems.
• Knowledge of monitoring and logging tools.
• Good problem-solving skills and the ability to troubleshoot complex issues.
• Excellent communication and collaboration skills.

AI And Intelligent Automation Skills

• Hands-on experience using AI-powered development assistants or coding tools to improve scripting, infrastructure automation, and troubleshooting productivity.
• Familiarity with AI-assisted log analysis, incident investigation, root cause analysis, and operational problem-solving.
• Understanding of Python scripting, REST APIs, and automation workflows for integrating DevOps tools with AI-powered services.
• Awareness of the limitations of AI-generated outputs, including the need for validation, security checks, and human approval for production-impacting changes.
• Willingness to learn and experiment with AI agents, AI-powered observability, and intelligent automation in DevOps environments.

Good to Have

• Familiarity with AI agents and integrations with DevOps tools such as Jenkins, GitHub, Azure DevOps, Jira, or observability platforms through APIs or integration protocols such as MCP.
• Awareness of AI security practices, including least-privilege access, audit logging, protection of secrets, and approval controls for production-impacting actions.

We Are Not Looking For Someone Who

• Has only theoretical knowledge without hands-on practical experience.
• Lacks willingness to learn new tools, automation, AI-assisted workflows, or adapt to changing technologies.