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Join our team as a DevOps Engineer specializing in Artificial Intelligence (AI) and Large Language Model (LLM) infrastructure. You will play a critical role in architecting, deploying, and optimizing scalable AI platforms using modern DevOps practices and state-of-the-art tools.
Job Responsibility:
Build, automate, and manage CI/CD pipelines for deploying and maintaining AI/LLM workloads
Collaborate with AI engineers and data scientists to streamline model deployment, versioning, and monitoring
Design and maintain cloud infrastructure using Infrastructure as Code (IaC) platforms such as Terraform and Ansible
Orchestrate and manage containerized AI environments using Kubernetes
Implement robust monitoring and logging solutions utilizing Grafana and Prometheus
Optimize AI model inference and training workloads—especially for NVIDIA GPU-powered environments
Apply strict security and compliance standards for all infrastructure components
Diagnose and resolve production issues, continuously improving reliability and scalability of AI services
Requirements:
Proven experience as a DevOps Engineer, preferably supporting AI or machine learning platforms
Hands-on expertise with Kubernetes (EKS, AKS, GKE, or on-prem), Docker, Terraform, and Ansible
Experience with monitoring/observability tools such as Grafana and Prometheus
Familiarity with NVIDIA GPU drivers, CUDA, and hardware provisioning for machine learning tasks
Proficiency in at least one scripting language (Python, Bash, etc.)
Cloud platform experience (AWS, GCP, Azure)
hybrid/on-premise a plus
Previous work with MLOps tools and data pipeline automation is highly desirable
Bachelor’s degree in Computer Science or related field, or equivalent professional experience
Nice to have:
Previous work with MLOps tools and data pipeline automation is highly desirable