We are looking for an enthusiastic and detail-oriented DevOps Engineer to join our team. The ideal candidate should have a solid foundation in DevOps practices, cloud infrastructure, and deployment pipelines, along with exposure to artificial intelligence (AI) technologies. This role will support the automation and optimization of AI model deployment and cloud-based infrastructure, ensuring seamless integration between development, operations, and AI initiatives.
Job Responsibilities
Develop, deploy, monitor, optimize and maintain build and release pipelines.
Support developments teams on branching and versioning approaches
Creating packages, builds, releases and patches as well as the software deliverables for the customers.
Assist in the design, implementation, and management of DevOps pipelines for deploying and maintaining AI models and services.
Automate the deployment of AI applications and models into cloud environments (AWS, Azure, GCP, etc.).
Work with AI and Data Science teams to ensure seamless integration of machine learning workflows into production environments.
Implement CI/CD pipelines for continuous testing and deployment of AI models and applications.
Collaborate with cross-functional teams to troubleshoot and resolve issues related to the integration of AI models, data pipelines, and infrastructure.
Support infrastructure as code (IaC) practices using tools like Terraform, Ansible, or CloudFormation.
Maintain and optimize cloud infrastructure for cost-efficiency and scalability, particularly for AI workloads.
Participate in the implementation of containerization and orchestration technologies (Docker, Kubernetes) for All applications.
Stay updated with the latest trends in DevOps and AI, recommending best practices for improvement.
Work with QA teams to improve efficiency of automation runs by exploring innovative approaches like parallelization/auto scaling etc.
Job Qualification
BE/BTech or ME/MTech with 2+ years of experience in DevOps.
Strong knowledge of DevOps concepts, continuous integration, continuous deployment, and automation.
Experience with cloud platforms (AWS, GCP, Azure) and cloud services (EC2, Lambda, Kubernetes, etc.).
Familiarity with containerization tools such as Docker and Kubernetes.
Exposure to AI/ML concepts, including deployment of machine learning models and managing AI workloads.
Proficiency in scripting languages (Python, Shell, Bash, etc.).
Experience with infrastructure as code (IaC) using tools like Terraform, Ansible, or CloudFormation.
Basic knowledge of version control systems (Git).
Familiarity with monitoring and logging tools such as Prometheus, Grafana, ELK Stack, or similar.
Understanding of data pipeline and ETL processes for AI and ML systems.
Soft Skills:
Strong analytical and problem-solving skills.
Excellent communication and collaboration skills.
Ability to work in a fast-paced and evolving environment.
A passion for learning new technologies and growing in the DevOps and AI space.
