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Ethara AI Linkedin · Posted 2d ago

Sr. DevOps Engineer

India

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Senior DevOps Engineer:

Company: Ethara AI

Location: 5th Floor, Plot No. 273, Udyog Vihar II Road, Udyog Vihar Phase 1, Sector 20, Gurugram, Haryana 122016

Employment Type: Full-Time

Experience Required: 5+ Years


Role Overview

We are looking for a highly skilled Senior DevOps Engineer with strong expertise in cloud infrastructure, containerization, and automation. In this role, you will be responsible for designing, deploying, and managing scalable, secure, and high-performance infrastructure that supports AI-driven platforms and production-grade systems.

You will play a key role in driving DevOps maturity, implementing best practices, and enabling seamless deployment and observability across distributed systems.


Key Responsibilities

  • Design and manage scalable, secure cloud infrastructure on AWS, including VPC, IAM, EC2, S3, RDS, ECR, Route 53, and Secrets Manager
  • Build and maintain Infrastructure as Code (IaC) using Terraform, Pulumi, or AWS CDK
  • Develop and manage CI/CD pipelines using Git, GitHub Actions, Jenkins, and ArgoCD with GitOps practices
  • Design, build, and optimize containerized applications using Docker, including image creation, multi-stage builds, and runtime optimization, and deploy them on Kubernetes (EKS) using Helm, HPA, RBAC, and IRSA
  • Own end-to-end container lifecycle management, including image optimization, security hardening, versioning, and efficient deployment across environments
  • Implement advanced Kubernetes capabilities such as Karpenter, Istio service mesh, mTLS, and canary deployments
  • Set up and manage observability and monitoring systems using CloudWatch, Prometheus, Grafana, Loki, and OpenSearch
  • Design and manage streaming and messaging systems using Kafka, MSK, and Schema Registry
  • Ensure robust security practices, including IAM policies, container security, TLS/SSL, and shift-left security approaches
  • Handle incident management, perform root cause analysis (RCA), and improve system reliability
  • Optimize infrastructure for cost, performance, and scalability
  • Collaborate with engineering and AI teams to support LLM infrastructure and deployment workflows, including AWS Bedrock integration


Required Skills & Qualifications

  • 5+ years of experience in DevOps / Cloud / Infrastructure Engineering
  • Strong hands-on experience with AWS services: VPC, IAM, EC2, S3, RDS, ECR, Route 53, Secrets Manager
  • Strong hands-on experience with Docker, including containerization, image optimization, multi-stage builds, and debugging containerized environments
  • Deep expertise in Kubernetes (EKS), including Helm, HPA, RBAC, IRSA, Karpenter, and Istio
  • Strong experience with CI/CD tools: Git, GitHub Actions, Jenkins, ArgoCD
  • Hands-on experience with Infrastructure as Code tools such as Terraform (preferred), Pulumi, or AWS CDK
  • Experience with monitoring and observability tools: CloudWatch, Prometheus, Grafana, Loki, OpenSearch
  • Working knowledge of Kafka/MSK and distributed streaming systems
  • Strong understanding of Linux systems, networking, DNS, TLS/SSL, ALB/NLB
  • Proficiency in scripting (Python and/or Bash)
  • Strong understanding of security best practices (IAM, RBAC, container security)
  • Experience in incident management and reliability engineering


Preferred / Bonus Skills

  • Experience with AWS Bedrock and AI/ML infrastructure
  • Familiarity with service mesh (Istio) and mTLS architectures
  • Exposure to MLOps tools such as Kubeflow or MLflow
  • Proven experience in cost optimization at scale
  • Prior experience working in AI/LLM-driven environments


Certifications (Preferred)

  • AWS Solutions Architect certifications
  • Certified Kubernetes Administrator (CKA) or Developer (CKAD)
  • Terraform Associate Certification
  • DevSecOps or Security+ Certification


Why Join Us

  • Work on cutting-edge AI/ML infrastructure and LLM systems
  • Design and scale production-grade distributed systems
  • Be part of a high-growth, high-impact engineering team
  • Opportunity to shape DevOps architecture and best practices
  • Competitive compensation and continuous learning opportunities

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