InfoBeans Technologies - DevOps Engineer - Kubernetes/Docker
InfoBeans
We are looking for an experienced DevOps Engineer with expertise in CI/CD, Kubernetes, cloud-native infrastructure, and application reliability, along with hands-on exposure to Java/Spring Boot and Generative AI. The role involves automating deployment and operational workflows, supporting distributed applications, improving system reliability and performance, and leveraging AI-driven solutions to enhance troubleshooting and engineering productivity.
Key Responsibilities
- Design, build, maintain, and optimize CI/CD pipelines to enable reliable and automated software delivery.
- Manage and support Kubernetes/OpenShift environments, including deployments, configuration, scaling, monitoring, and troubleshooting.
- Support and troubleshoot Java/Spring Boot applications running in distributed and microservices-based environments.
- Improve application and infrastructure reliability, availability, performance, and scalability through DevOps and SRE practices.
- Monitor system health using logs, metrics, dashboards, alerts, and observability tools.
- Participate in incident management, root-cause analysis, problem management, and operational improvement initiatives.
- Automate deployment, infrastructure management, monitoring, testing, and repetitive operational tasks.
- Apply Generative AI, LLMs, and AI agents to support incident analysis, troubleshooting, monitoring, test automation, and operational workflows.
- Integrate AI services such as Azure OpenAI with existing applications and operational tools through APIs.
- Work with engineering and platform teams to improve application deployment, release management, and production support processes.
- Troubleshoot issues across Linux environments, application services, APIs, JVMs, databases, and containerized infrastructure.
- Support microservices and REST API integrations, including debugging connectivity, configuration, and performance issues.
- Follow security, reliability, automation, and infrastructure management best practices.
- Maintain technical documentation, runbooks, deployment procedures, and incident-resolution guides.
- Identify opportunities to improve operational efficiency through platform engineering, automation, and AI-assisted workflows.
- 5 - 10 years of experience in DevOps, Site Reliability Engineering (SRE), platform engineering, or infrastructure automation.
- Strong hands-on experience with CI/CD pipelines, Kubernetes, and microservices.
- Experience with OpenShift or equivalent container orchestration platforms.
- Working knowledge of Java and Spring Boot applications, including application troubleshooting and deployment support.
- Strong understanding of Linux administration, shell scripting, and system troubleshooting.
- Good knowledge of REST APIs, SQL, JVM fundamentals, application logs, monitoring, and distributed systems.
- Experience with infrastructure and application monitoring, incident management, and root-cause analysis.
- Practical exposure to Generative AI, LLMs, Azure OpenAI, or AI agents.
- Experience integrating APIs and automating workflows using AI services or other external platforms.
- Strong understanding of application reliability, performance optimization, scalability, and production operations.
- Familiarity with Git, automated testing, deployment strategies, and secure DevOps practices.
- Strong analytical, troubleshooting, and problem-solving skills.
- Good communication and collaboration skills, with the ability to work across DevOps, Development, QA, and platform teams.