Senior DevOps Engineer (Azure and AWS)

0 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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On-site

Job Type

Full Time

Job Description

Minimum Experience - 10 yrs


About the Role

Cloud & Infrastructure Architect


Key Responsibilities

Cloud & Infrastructure Architecture

  • Design secure, resilient, and high-performance cloud architectures on AWS.
  • Support integration with GCP, Azure, and on-premise infrastructure (VMware, OpenStack).
  • Define hybrid cloud strategies covering security, identity federation, and data governance.
  • Develop infrastructure blueprints and reference architectures aligned with business needs.

Infrastructure as Code & Automation

  • Champion Infrastructure as Code (IaC) using Terraform, CloudFormation, or Pulumi.
  • Automate environment provisioning and configuration using Ansible, Helm, etc.
  • Establish GitOps pipelines for consistency, change tracking, and governance.

DevOps & Continuous Delivery

  • Architect and manage CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or ArgoCD.
  • Embed security and compliance into the software delivery lifecycle (DevSecOps).
  • Implement release strategies like blue/green, canary deployments, and feature flagging.

Hybrid Infrastructure & On-Premise Integration

  • Lead integration of on-prem systems with cloud-native services.
  • Manage container platforms, virtualized environments, and legacy applications.
  • Enforce disaster recovery, backup, and failover strategies across hybrid deployments.

Monitoring, SRE & Reliability Engineering

  • Define and monitor SLAs, SLIs, and SLOs; implement proactive alerting and auto-remediation.
  • Operationalize observability using Prometheus, Grafana, ELK, CloudWatch, Datadog.
  • Drive incident response, RCA, and post-mortem processes for continuous improvement.

AI/ML Platform Enablement (Preferred)

  • Collaborate with data and ML teams to provision infrastructure for AI/ML workloads.
  • Support orchestration frameworks like Kubeflow, MLflow, Airflow, and cloud-native ML services.
  • Optimize infrastructure for data ingestion, feature engineering, and real-time inference.


Technical Skills

  • AWS Certifications: DevOps Engineer – Professional, Solutions Architect – Professional.
  • Experience with data platforms, AI/ML pipelines, and high-volume data lake architectures.
  • Familiarity with ITIL, SRE principles, and compliance standards (ISO 27001, SOC2, GDPR).
  • Expertise in cloud cost optimization and FinOps best practices.


Behavioral Competencies

  • Strategic Thinking:

    Ability to define scalable architectures aligned with business growth.
  • Technical Leadership:

    Influences cross-functional decisions and promotes engineering excellence.
  • Security-First Mindset:

    Prioritizes resilience, auditability, and compliance.
  • Communication:

    Comfortable presenting complex technical topics to diverse audiences.

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