Xcelpros - DevOps Engineer - Cloud Infrastructure

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Posted:2 weeks ago| Platform: Linkedin logo

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Job Type

Part Time

Job Description

Description

Job Title : Devops EngineerExperience : 5+yrsEmployment type : Part TimeTimings : It would be for 3 - 4 hours on a daily basis starting from 7pm onwards

Key Responsibilities

Cloud Infrastructure Management (Azure & AWS) :
  • Manage and scale cloud-based environments, ensuring high availability, fault tolerance, and security.
  • Implement and maintain multi-tenant architectures in cloud platforms (Azure and AWS), ensuring resource isolation and efficient cost management.
  • Configure and optimize resources across both Azure and AWS platforms, leveraging best practices for cloud security, networking, and performance.

CI/CD Pipeline Maintenance

  • Design, implement, and optimize continuous integration and continuous deployment (CI/CD) pipelines across development, staging, and production environments.
  • Ensure high availability and minimal downtime for production releases by automating rollbacks, canary deployments, and blue-green deployments.
  • Integrate monitoring and alerting into the pipelines to catch issues before they reach production.

AI/ML Ops Integration

  • Work closely with the AI/ML teams to deploy and monitor machine learning models in production environments, ensuring smooth integration with CI/CD pipelines.
  • Implement and maintain automated workflows for ML model training, testing, and deployment.
  • Use tools like Azure ML, SageMaker, or other relevant services to enable ML lifecycle management.

Test-Driven Development (TDD) Integration

  • Promote and implement Test-Driven Development (TDD) practices within CI/CD pipelines to improve software quality and reduce defects in production.
  • Ensure that code quality is maintained by integrating automated unit and integration tests into the pipelines, along with ensuring that sufficient test coverage is in place.

Automation & Scripting

  • Develop automation scripts and tools to streamline repetitive tasks across various environments.
  • Implement Infrastructure as Code (IaC) using tools like Terraform, CloudFormation, or ARM Templates.
  • Create and manage cloud-native services such as Kubernetes (AKS, EKS), containerized applications, and serverless architectures.

Monitoring & Performance Tuning

  • Set up and manage monitoring systems (e.g., Azure Monitor, CloudWatch, Prometheus, Grafana) for tracking system performance, cost, and security metrics.
  • Implement logging and alerting systems to ensure rapid detection of issues in production.
  • Continuously improve infrastructure performance by analyzing bottlenecks and resource optimization opportunities.

Collaboration & Mentoring

  • Collaborate with software engineers to ensure smooth integration of new code into the pipelines, supporting Agile development cycles.
  • Provide guidance and mentorship to junior DevOps engineers and developers on best practices for cloud infrastructure, CI/CD, and automation.

Security & Compliance

  • Ensure cloud infrastructure complies with industry standards for security, privacy, and governance.
  • Implement security best practices, including identity and access management (IAM), encryption, and network security.

Essential

Skills & Qualifications :

Cloud Experience

  • Extensive experience with Azure and AWS cloud platforms, with a strong understanding of their respective services (e.g., Azure Kubernetes Service, AWS EC2, S3, Lambda, CloudFormation, and Azure Resource Manager).
  • Experience with multi-tenant architecture at scale on cloud platforms, including designing isolated environments and managing cross-tenant resources.

CI/CD & Automation

  • Strong experience with CI/CD tools such as Jenkins, GitLab CI, Azure DevOps, or AWS CodePipeline.
  • Familiarity with Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Azure ARM templates.
  • Proficient in containerization technologies such as Docker, Kubernetes, and container orchestration platforms (AKS, EKS).

AI/ML Ops Knowledge

  • Familiarity with AI/ML Ops practices and tools (e.g., Azure Machine Learning, AWS SageMaker, MLFlow, Kubeflow).
  • Experience automating the deployment and monitoring of machine learning models in production environments.

Programming & Scripting

Strong programming skills in languages such as Python, Go, or Ruby.Experience with scripting in Bash, PowerShell, or Python for automating tasks.

Test-Driven Development (TDD)

  • Proven experience integrating Test-Driven Development (TDD) into CI/CD pipelines.
  • Familiarity with testing frameworks like JUnit, pytest, Mocha, or equivalent for unit, integration, and functional tests.

Monitoring & Logging

  • Experience with monitoring tools such as Prometheus, Grafana, CloudWatch, Azure Monitor, and Datadog.
  • Familiarity with logging frameworks such as ELK Stack, Fluentd, or Splunk.
  • Security Best Practices :
  • Experience with cloud security practices, including IAM, security groups, VPNs, and encryption standards.
(ref:hirist.tech)

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