AI DevOps Engineer

Job highlights

• We are seeking an experienced AI Engineer with strong AI DevOps expertise to join our team and drive the development,deployment,and operationalization of enterprise AI solutions. . Education: BE,B Tech,MSc,MCA or equivalent degree in Computer Science,Electronics or related discipline
• Required Qualifications
• Experience with REST APIs,microservices,and distributed systems.

We are seeking an experienced AI Engineer with strong AI DevOps expertise to join our team and drive the development, deployment, and operationalization of enterprise AI solutions.

Education: BE, B Tech, MSc, MCA or equivalent degree in Computer Science, Electronics or related discipline.

Required Qualifications

• Bachelors or Masters degree in Computer Science, Engineering, Data Science/related field.
• 3+ years of software engineering experience.
• 2+ years of experience working on DevOps or Generative AI solutions.
• Strong programming skills in Python and/or C#.
• Experience with REST APIs, microservices, and distributed systems.
• Experience with CI/CD tools and DevOps practices.
• Experience with Docker, Terraforms and Kubernetes.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Strong understanding of AI/ML lifecycle management and deployment practices.
• Excellent analytical, troubleshooting, and communication skills.

AI DevOps MLOps

• Design, implement, and maintain CI/CD pipelines for AI and software applications.
• Automate model deployment, testing, monitoring, and release processes.
• Establish best practices for AI DevOps, MLOps, infrastructure environment management.
• Monitor and optimize AI application performance, scalability, reliability, and security.
• Implement observability, logging, and governance frameworks for AI services.

AI Solution Development

• Design, develop, and maintain AI/GenAI applications and services.
• Build and integrate AI solutions using LLMs, AI frameworks, and enterprise platforms.
• Collaborate with product owners, architects, and engineering teams to translate business requirements into AI-enabled solutions.
• Develop APIs, services, and reusable components supporting AI workloads.

AI Cloud Platform Engineering

• Deploy and manage AI solutions across cloud environments.
• Build and maintain containerized applications using Kubernetes and Docker.
• Support infrastructure-as-code and automation initiatives.
• Ensure high availability and operational excellence across development, testing, and production environments.

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.