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.
