Sr. DevOps Engineer

Job Description

Job Description

The role also involves supporting enterprise compliance requirements and enabling infrastructure for AI and LLM-driven workloads.

If you have strong expertise in AWS, Kubernetes, CI/CD, and Infrastructure as Code, and enjoy improving system reliability through automation and best practices, this role is a strong fit.

• 4–5 years of hands-on experience in DevOps, SRE, or Platform Engineering.
• Strong expertise in AWS (certification mandatory).
• Exposure to Azure is a plus.
• Deep understanding of AWS services, including VPC, IAM, EC2, EKS, ALB/NLB, S3, CloudFront, and RDS.
• Strong experience with Jenkins (mandatory).
• Hands-on experience with GitLab CI/CD.
• Experience integrating SonarQube for code quality and security checks.
• Strong experience with Docker and Kubernetes (EKS) in production environments.
• Understanding of container security, scaling, and networking.
• Hands-on experience with Terraform and Ansible (mandatory).
• Strong scripting skills in Bash and Python, with an automation-first mindset.
• Strong experience with monitoring and logging tools, including ELK stack, Nagios, and CloudWatch.
• Strong understanding of logs, metrics, traces, and alerting systems.
• Understanding of AI, LLM workloads, and infrastructure implications for Agentic AI systems.
• Exposure to AI workloads, vector databases, or GPU-based systems is a plus.
• Proven experience supporting production, customer-facing SaaS platforms.
• Strong troubleshooting skills across infrastructure, networking, and application layers.
• Strong communication and collaboration skills.

• Design, build, and operate highly available and scalable cloud infrastructure, primarily on AWS.
• Own and enhance CI/CD pipelines using Jenkins and GitLab, ensuring secure and reliable releases.
• Manage and optimize Dockerized applications and Kubernetes (EKS) clusters.
• Implement Infrastructure as Code using Terraform and Ansible.
• Drive automation-first practices using Bash and Python.
• Ensure platform reliability, performance, and observability using monitoring and logging tools.
• Operate and optimize logging, monitoring, and alerting systems, including ELK, Nagios, and CloudWatch.
• Enforce security best practices, vulnerability remediation, and compliance across environments.
• Collaborate with engineering, QA, security, and product teams to support smooth release cycles.
• Support AI, LLM-driven, and Agentic AI workloads and understand their infrastructure implications.
• Participate in incident management, root cause analysis, and continuous improvement initiatives.