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