Manager, DevOps Engineering

Position Summary: The role focuses on managing and optimizing the deployment, monitoring, and maintenance of AI systems and infrastructure, with a strong emphasis on reliability, scalability, and continuous improvement. This position plays a critical role in enabling seamless AI operations by implementing DevOps best practices, including CI/CD, containerization, and cloud orchestration. The role collaborates closely with AI architects, Platform Ops team, data scientists, and development teams to ensure smooth integration of AI models into production environments and high system performance. Who were looking for: PrimaryResponsibilities: Manage and optimize the deployment, monitoring, and maintenance of AI systems and infrastructure for scalable and reliable operations Implement and maintain CI/CD pipelines to enable efficient and secure delivery of AI solutions Collaborate with development teams and Platform Ops to integrate AI models and tools into production workflows and enterprise systems Monitor system performance and troubleshoot issues to ensure high availability and reliability of AI environments Automate routine operational tasks to increase efficiency and reduce downtime Ensure compliance with enterprise security and privacy standards in all AI operations Establish and maintain infrastructure-as-code and configuration management standards for AI products and platforms. Support the development and implementation of AI DevOps tooling, dashboards, and observability systems Work with cross-functional stakeholders to provide support and training for AI deployment processes Contribute to the continuous improvement of DevOps practices and tooling, aligned with enterprise engineering standards Skill: Directly contributes to operational reliability, performance, and security of enterprise AI systems Bachelors degree in computer science, Engineering, or a related field; masters degree preferred 5 years of professional experience in DevOps engineering or a related field Proficiency in DevOps practices and tools, including CI/CD pipelines, infrastructure-as-code, containerization, and orchestration (e.g., Docker, Kubernetes) Experience with cloud platforms and infrastructure management (e.g., Google Cloud, AWS, Azure) Github and GCP exp. Strong understanding of AI systems architecture, operations, and production deployment lifecycles Experience supporting AI/ML systems in production is a strong plus Knowledge of monitoring, observability, and logging tools such as Datadog or New Relic to ensure reliability and performance Ability to work collaboratively across engineering, architecture, and data science teams Solid problem-solving skills and a proactive approach to improving system operations and automation Strong written and verbal communication skills to document processes and share knowledge across teams Work location: Hyderabad, India Work hours: Work pattern: Full time role. Work mode: Hybrid.

Location: hyderabad, IN

Posted Date: 6/12/2025