Senior Devops Engineer

Senior DevOps Engineer Overview

• Lead the design and optimization of DevOps pipelines supporting AI/ML lifecycle processes and scalable cloud-based infrastructure.
• Collaborate with cross-functional teams to deliver secure, efficient, and innovative AI platforms and services.
• Automate infrastructure provisioning and management using advanced tools like Terraform and Kubernetes.
• Ensure reliability, scalability, and observability of AI systems and workloads in production environments.
• Implement security, compliance, and governance standards for AI systems and processes.
• Support production workloads for Generative AI systems and LLM-based services with a focus on performance and efficiency.
• Document standards, best practices, and processes for DevOps and AI infrastructure to ensure consistency and quality.
• Drive innovation by leveraging cutting-edge technologies and methodologies to enhance operational capabilities.

Senior DevOps Engineer Key Responsibilities & Duties

• Design and operate scalable DevOps pipelines for model lifecycle automation and deployment in cloud environments.
• Develop and manage cloud-native infrastructure using Kubernetes and containerized workloads on AWS.
• Implement systems for model versioning, artifact management, and experiment tracking to streamline AI workflows.
• Ensure system health monitoring, model performance tracking, and drift detection for AI systems.
• Collaborate with AI/ML engineers to standardize deployment patterns and practices for enhanced efficiency.
• Participate in incident response, troubleshooting, and continuous improvement initiatives to maintain system integrity.
• Optimize costs for compute-intensive workloads while ensuring scalability and operational efficiency.
• Document reference architectures and best practices for AI infrastructure and operations to guide future development.

Senior DevOps Engineer Job Requirements

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