Valiance Solutions - Software Engineer - DevOps

Responsibilities :

• 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.
• Application Deployment : Collaborate with the development teams to design and execute efficient and reliable application deployment processes.
• Infrastructure Automation : Automate infrastructure provisioning and configuration tasks, including VPC setup, server configuration, and network endpoint configuration.
• Containerization : Assist in containerizing applications using Docker, ensuring scalability, portability, and security.
• Continuous Integration / Continuous Deployment (CI / CD) : Implement and enhance CI / CD pipelines to streamline the application deployment process.
• Monitoring and Logging : Set up monitoring and logging solutions to ensure the smooth functioning of deployed applications and identify performance bottlenecks.
• Security : Work closely with the security team to implement best practices for securing cloud-based applications and infrastructure.
• Troubleshooting and Support : Collaborate with cross-functional teams to troubleshoot and resolve any infrastructure or deployment-related issues.
• Documentation : Maintain detailed documentation of infrastructure and deployment processes, ensuring knowledge sharing and seamless :
• Educational Background : Bachelor's degree in Computer Science, Engineering, or a related field.
• Experience : 3 to 5 years of relevant experience in DevOps, cloud automation, and application deployment.
• DevOps Tools : Proficiency with popular DevOps tools and technologies such as Git, Jenkins, Ansible, Terraform, Kubernetes, etc.
• 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.
• Docker : Solid understanding and practical experience with Docker containerization for application deployment.
• AI / ML and Models : Familiarity with AI / ML concepts and experience in deploying applications that use pre-trained or custom models will be advantageous.
• Scripting and Automation : Proficient in scripting languages such as Python, Bash, or Shell for automating tasks.
• Networking : Knowledge of networking concepts and experience in configuring network endpoints and VPCs.
• Problem-Solving : Strong analytical and problem-solving skills to diagnose and resolve technical issues.
• Communication : Excellent communication and collaboration skills to work effectively with cross-functional teams and clients.
• 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

(ref : hirist.tech)