Senior Devops Engineer

Overview

• Lead the design and operation of MLOps pipelines supporting AI/ML lifecycle processes.
• Collaborate with cross-functional teams to deliver scalable and secure AI platforms.
• Develop and maintain CI/CD pipelines for AI/ML services and infrastructure.
• Automate infrastructure provisioning using Infrastructure as Code tools like Terraform.
• Ensure reliability, scalability, and observability of AI platforms and workloads.
• Implement security, compliance, and governance requirements for AI systems.
• Support production workloads for Generative AI systems and LLM-based services.
• Document standards and best practices for MLOps and AI infrastructure.

Key Responsibilities & Duties

• Design and operate scalable MLOps pipelines for model lifecycle automation.
• Develop cloud-native infrastructure on AWS using Kubernetes and containerized workloads.
• Implement model versioning, artifact management, and experiment tracking.
• Ensure system health monitoring, model performance tracking, and drift detection.
• Collaborate with AI/ML engineers to standardize deployment patterns.
• Participate in incident response and continuous improvement initiatives.
• Optimize costs for compute-intensive workloads and ensure scalability.
• Document reference architectures and best practices for AI infrastructure.

Job Requirements

• Bachelor of Science degree in a relevant field is required.
• 15+ years of experience in DevOps, SRE, or Platform Engineering roles.
• Proficiency in AWS cloud services, Kubernetes, and CI/CD pipeline development.
• Hands-on experience with Terraform and scripting/programming languages like Python.
• Experience with MLOps platforms, model registries, and experiment tracking.
• Exposure to Generative AI workloads and LLM-based services in production.
• Strong communication skills and ability to work across teams effectively.
• AWS certifications are preferred but not mandatory.