DevOps Engineer

Location

On-site

Type

Full Time

Overview

We are looking for an experienced DevOps Engineer to design, implement, and optimize cloud based infrastructure for AI-powered applications. The ideal candidate should have expertise in CI/CD, cloud automation, containerization, and security practices in AWS, Azure, or GCP environments.

Key Responsibilities

  • Develop and maintain CI/CD pipelines for AI/ML applications

  • Automate cloud infrastructure provisioning using Terraform, CloudFormation, or ARM templates

  • Manage and optimize containerized workloads using Docker and Kubernetes

  • Ensure high availability, scalability, and security of AI-driven cloud applications

  • Collaborate with AI engineers, software developers, and cloud architects

  • Monitor system performance, troubleshoot issues, and implement best practices for cloud security

  • Implement AI-driven automation and observability solutions using tools like Prometheus, Grafana, or ELK stack

  • Stay updated with the latest DevOps, AI, and cloud computing trends

Required Skills & Qualifications

  • Bachelor's or Master’s degree in Computer Science, Engineering, or a related field

  • 3+ years of experience in DevOps, cloud computing, or infrastructure automation

  • Proficiency in AWS, Azure, or GCP cloud services

  • Hands-on experience with CI/CD tools (Jenkins, GitHub Actions, GitLab CI/CD, and Azure DevOps)

  • Strong knowledge of containerization (Docker, Kubernetes, Helm)

  • Experience with scripting and automation using Python, Bash, or PowerShell

  • Familiarity with monitoring and logging tools (Prometheus, Grafana, Splunk, ELK stack)

  • Knowledge of security best practices for DevOps and cloud infrastructure

  • Certifications in AWS (AWS Certified DevOps Engineer), Azure (Azure DevOps Engineer), or GCP (Google Professional DevOps Engineer)

  • Experience with MLOps and AI model deployment in cloud environments

  • Knowledge of infrastructure-as-code (IaC) best practices

  • Experience in serverless computing and event-driven architectures

  • Experience integrating AI/ML pipelines with cloud-based DevOps workflows

  • Knowledge of serverless computing and event-driven architectures

  • Cloud certifications such as AWS DevOps Engineer, Azure DevOps Engineer Expert, or Google Professional DevOps Engineer

Submit your Application

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