Job Description:

We are seeking a talented and motivated Software Engineer with expertise in DevOps tools and cloud automation to join our team. As a Software Engineer, you will play a crucial role in automating the IT infrastructure and application deployment processes for AI/ML-based applications utilizing pre-trained and custom models. The primary focus will be on deploying applications on cloud platforms using Docker containers and handling various infrastructure automation tasks, such as configuring VPCs, attaching disks to servers, and setting up network endpoints.

Responsibilities:

1. DevOps and Cloud Automation: Implement and maintain automation pipelines for the deployment of AI/ML-based applications on cloud platforms (e.g., AWS, Azure, GCP) using Docker containers.
2. Application Deployment: Collaborate with the development teams to design and execute efficient and reliable application deployment processes.
3. Infrastructure Automation: Automate infrastructure provisioning and configuration tasks, including VPC setup, server configuration, and network endpoint configuration.
4. Containerization: Assist in containerizing applications using Docker, ensuring scalability, portability, and security.
5. Continuous Integration/Continuous Deployment (CI/CD): Implement and enhance CI/CD pipelines to streamline the application deployment process.
6. Monitoring and Logging: Set up monitoring and logging solutions to ensure the smooth functioning of deployed applications and identify performance bottlenecks.
7. Security: Work closely with the security team to implement best practices for securing cloud-based applications and infrastructure.
8. Troubleshooting and Support: Collaborate with cross-functional teams to troubleshoot and resolve any infrastructure or deployment-related issues.
9. Documentation: Maintain detailed documentation of infrastructure and deployment processes, ensuring knowledge sharing and seamless handover.

Requirements:

1. Educational Background: Bachelor's degree in Computer Science, Engineering, or a related field.
2. Experience: 3 to 5 years of relevant experience in DevOps, cloud automation, and application deployment.
3. DevOps Tools: Proficiency with popular DevOps tools and technologies such as Git, Jenkins, Ansible, Terraform, Kubernetes, etc.
4. Cloud Platforms: Strong hands-on experience with at least one major cloud platform (e.g., AWS, Azure, GCP) and familiarity with cloud services such as EC2, S3, VPC, etc.
5. Docker: Solid understanding and practical experience with Docker containerization for application deployment.
6. AI/ML and Models: Familiarity with AI/ML concepts and experience in deploying applications that use pre-trained or custom models will be advantageous.
7. Scripting and Automation: Proficient in scripting languages such as Python, Bash, or Shell for automating tasks.
8. Networking: Knowledge of networking concepts and experience in configuring network endpoints and VPCs.
9. Problem-Solving: Strong analytical and problem-solving skills to diagnose and resolve technical issues.
10. Communication: Excellent communication and collaboration skills to work effectively with cross-functional teams and clients.
11. Cloud Certifications: Relevant cloud certifications (e.g., AWS Certified DevOps Engineer, Azure DevOps Engineer) will be a plus.

This is a fantastic opportunity to join a dynamic team and work on cutting-edge AI/ML-based applications in a fast-paced and collaborative environment. If you are passionate about DevOps, cloud automation, and AI/ML technologies, and have the drive to deliver high-quality results, we encourage you to apply.