[Remote] Senior AI Infrastructure Engineer at TetraScience

The Senior AI Infrastructure Engineer will design, implement, and maintain cloud-native infrastructure to support AI and data workloads, with a focus on AI and data platforms such as Databricks and AWS Bedrock. They will build and manage scalable data pipelines to ingest, transform, and serve data for ML and analytics. Responsibilities include developing infrastructure-as-code using tools like Cloudformation and AWS CDK to ensure repeatable and secure deployments. The engineer will collaborate with AI engineers, data engineers, and platform teams to improve the performance, reliability, and cost-efficiency of AI models in production. Driving best practices for observability, including monitoring, alerting, and logging for AI platforms, is a key duty. The role also involves contributing to the design and evolution of the AI platform to support new ML frameworks, workflows, and data types, and staying current with new tools and technologies to recommend improvements to architecture and operations. Integrating AI models and large language models (LLMs) into production systems to enable use cases using architectures like retrieval-augmented generation (RAG) is also part of the role.