Senior AIOps Engineer I

Role overview Keep production AI and machine learning services reliable, observable, secure, and cost-aware. You’ll work with product, platform, data science, and machine learning teams on model monitoring, deployment practices, incident response, and the infrastructure needed to ship AI features safely.

Responsibilities - Track service availability and performance, and define reliability measures such as latency, errors, and model quality. - Coordinate model refreshes, including retraining, validation, and redeployment, to address staleness and drift. - Build monitoring, logging, and alerting for models and data pipelines. - Help operate and evolve AI infrastructure, including large-scale batch inference and retrieval-augmented generation systems. - Respond to production incidents and improve deployment pipelines.

Requirements - The role involves production AI and machine learning operations, including reliability and observability. - The stated environment uses Python, Kubernetes, and Google Cloud Platform. - Work calls for collaboration with product, platform, data science, and machine learning colleagues.