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Senior AWS DevOps Engineer

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Onsite

Senior AWS DevOps Engineer

Edge Executive Search

Senior AWS DevOps Engineer

Skills

Data EngineeringDockerPythonDevOpsAmazon EC2AWS LambdaDatabricksMachine LearningAIAWSKubernetesTerraform

15 days ago

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Important information


Contract type:

Permanent

Location:

Gurugram, Haryana, India

Work mode:

Onsite

Published on:

7 October 2026

What they need


Roles and Responsibilities :

  • Design, deploy, and maintain secure, scalable AWS cloud infrastructure, Kubernetes platforms, Terraform modules, and core networking/services to support reliable data engineering operations.
  • Implement, manage, and optimize CI/CD pipelines, Infrastructure as Code, deployment automation, security validation, automated testing, and release reliability practices.
  • Operate Databricks, AI/ML, and generative AI workloads through platform administration, environment provisioning, deployment automation, monitoring, rollback, MLOps, and LLMOps practices.
  • Implement monitoring, observability, AIOps, anomaly detection, event correlation, alerting, incident triage, log analysis, root-cause analysis, and remediation recommendations.
  • Build automation using Python, Bash, APIs, and event-driven services to reduce manual effort, improve operational efficiency, and strengthen platform reliability.
  • Apply cloud security, DevSecOps, responsible AI, governance controls, human approvals, auditability, and documentation practices across AI-enabled operational workflows.

Job Requirements :

  • 5-8 years of experience in AWS DevOps engineering with expertise in IAC (Infrastructure as Code) tools like Terraform.
  • Strong understanding of AWS services such as EC2, EKS, ECS, S3, RDS, Lambda etc.
  • Must have AWS infrastructure, Terraform, Kubernetes, CI/CD, Python/Bash, monitoring, cloud security, database, troubleshooting, communication, AI-assisted engineering, generative AI fundamentals, and responsible AI evaluation skills.
  • Must be hands-on with Generative AI (GenAI) and Agentic AI, with demonstrated daily use of AI-powered tools to enhance productivity, automate workflows, and solve business problems.
  • Experience with containerization using Docker and orchestration using Kubernetes.

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