As a full-time remote opportunity, the Senior AIOps Engineer will partner with product managers and engineers to ensure AI and ML systems are reliable and secure, focusing on monitoring performance, managing incidents, and evolving AI infrastructure.
Key responsibilities:
Own production reliability for AI/ML services, including monitoring availability and performance, and managing model refresh cycles
Design and implement monitoring, logging, and alerting systems for models and data pipelines, integrating metrics with observability tools
Streamline deployment workflows and improve CI/CD pipelines for AI services while provisioning and maintaining new AI infrastructure
Required qualifications:
4+ years of relevant experience, including at least 3 years in software engineering or production operations with Kubernetes and cloud platforms
Strong experience with Google Cloud Platform, particularly GKE, BigQuery, and Vertex AI
Hands-on experience with CI/CD tools, infrastructure-as-code tools, and monitoring/logging tools
Understanding of machine learning concepts and familiarity with LLM ecosystem tooling is a plus
Proficiency in Python and solid software engineering practices, including Test-Driven Development