DevOps Engineer - AI

Responsibilities:

• Design, build, and develop/enhance state of art machine Learning system infrastructure (cloud and on-premise) core components and architect platforms to create, train and deploy ML models.
• Build operating dashboards and charts to track system errors, performance and enable root cause analysis.
• Identify gaps and evaluate relevant tools and technologies as needed to improve processes and systems, leveraging open-source and cloud computing technologies to build effective solutions.
• Collaborate with the AI team to drive ML projects from conception to completion and production monitoring.

Requirements:

• Bachelors or above with a good academic background.
• 3-4 years of meaningful work experience in DevOps handling complex services.
• Strong troubleshooting skills to keep our services highly available.
• Strong expertise and experience with Google Cloud Platform (GCP), Docker, Kubernetes, CI/CD, and Jenkins.
• Extensive experience in designing, implementing, and maintaining infrastructure as code using preferably Terraform.
• Create and maintain deployment manifest files for microservices using HELM.
• Having LLMOps or MLOps experience is a bonus.
• Strong expertise required with deployment at scale on kubernetes cluster via HPA.
• Broad technical background and experience with architecture, design, and operations of cloud solutions and the how-to meet security compliance requirements.
• Monitoring system health, ensuring security, scalability, and reliability.
• Design, implement, and maintain observability, monitoring, logging, and alerting using the tools like Prometheus, Grafana, Promtail, Loki, Datadog.