We are seeking a highly motivated Senior DevOps Engineer with strong experience in designing, automating, and operating scalable, secure, and highly available cloud-native platforms. The role requires hands-on expertise across AWS, Kubernetes/EKS, Infrastructure as Code, CI/CD, observability, service mesh, databases, and production operations. The ideal candidate should also have a good understanding of Generative AI, LLM platforms, AI gateways, and practical AI adoption in DevOps/AIOps workflows.
Roles & Responsibilities
Design, build, operate, and scale highly available production infrastructure on AWS, with a strong focus on reliability, security, automation, and performance.
Manage and optimize Kubernetes/EKS environments, including cluster upgrades, autoscaling, workload scheduling, networking, security, resource management, and high availability.
Build and maintain reusable Infrastructure as Code using Terraform and implement automated infrastructure provisioning across multiple environments.
Design and maintain robust CI/CD pipelines using GitLab CI/CD, Jenkins, or similar tools for automated build, testing, deployment, rollback, and release management.
Implement and operate containerized workloads using Docker, Kubernetes, and Helm, following deployment and configuration best practices.
Manage service-to-service communication and traffic using Istio, Kubernetes Gateway API, kgateway, Envoy-based gateways, or similar technologies.
Build and maintain centralized observability platforms using Prometheus, Grafana, Loki, Cortex, and related monitoring, logging, alerting, and tracing tools.
Troubleshoot complex production issues across Kubernetes, Linux, networking, DNS, HTTP/TLS, service mesh, load balancers, databases, and distributed microservices.
Support and operate data platforms such as MySQL, PostgreSQL, RDS, ScyllaDB, ClickHouse, and Redis, including backup, replication, monitoring, and performance troubleshooting.
Drive platform reliability and operational excellence through incident management, root cause analysis, automation, capacity planning, cost optimization, and continuous improvement.
Adopt AI and AIOps capabilities in DevOps workflows for troubleshooting, log analysis, alert correlation, automation, incident analysis, documentation, and engineering productivity.
Required Skills
5-6 years of hands-on experience in DevOps, Cloud Infrastructure, SRE, or Platform Engineering roles.
Strong knowledge of AWS services including EKS, EC2, VPC, ALB/NLB, CloudFront, Route 53, IAM, S3, RDS, KMS, Secrets Manager, and security services.
Strong experience with Kubernetes, Docker, Helm, Terraform, GitLab CI/CD, and Jenkins.
Hands-on knowledge of Istio, service mesh, API gateways, Kubernetes Gateway API, and Envoy-based architectures.
Strong experience with observability tools such as Prometheus, Grafana, Loki, Cortex, and similar monitoring/logging platforms.
Strong Linux administration and troubleshooting skills, with scripting experience using Python and Shell.
Experience with relational and distributed databases including MySQL, PostgreSQL, RDS, ScyllaDB, ClickHouse, Redis, or similar technologies.
Familiarity with build and software development tools such as Git, Maven, Gradle, artifact repositories, and release processes.
Good understanding of Generative AI and LLM fundamentals, including prompts, tokens, context windows, model APIs, inference, latency, rate limits, and AI workload cost.
Familiarity with AI platforms and technologies such as OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, AI-gateway, or similar AI/LLM gateway solutions.
Responsible for safeguarding sensitive company data against unauthorized access, use, or disclosure, and for reporting any suspected security incidents in line with the organization's ISMS (Information Security Management System) policies and procedures.