Staff Software Engineer, Applied AI Engineering

Overview In this role you will architect secure, cost-efficient distributed systems and MLOps pipelines on GCP to support fine-tuning and serving frontier models. You translate AI/ML research into production-grade services, optimizing latency, throughput, and large-scale TPU/GPU usage. You will design robust multi-agent architectures and guardrailed workflows, shaping Google Cloud AI roadmap and mentoring senior engineers. You’ll bridge DeepMind, Research, and product teams to push scalable AI platforms forward and deliver high-impact enterprise solutions. ResponsibilitiesArchitect secure, cost-efficient distributed systems and MLOps pipelines on Google Cloud PlatformTranslate AI/ML research into production-grade services with optimization of latency and throughputDesign multi-agent architectures and cognitive planning engines for complex workflowsShape Google Cloud AI roadmap by feeding insights from incubation projects to core engineeringMentor executive engineers and foster rapid prototyping and rigorous system designDefine technical roadmaps, establish architectural standards, and engineer zero-to-one AI platformsManage multi-agent orchestration, reasoning pipelines, and multimodal models for scalable servicesCollaborate with DeepMind, Research, PM, and enterprise partners to translate breakthroughs into production systems Key requirementsBachelor's degree or equivalent practical experience8 years of software development experience5 years in testing and launching software products3 years in software design and architecture5 years leading ML design and ML infrastructure optimization2 years experience with GenAI techniques or related conceptsleadershipproblem-solvingexcellent communicationGoogle Cloud Platform (GCP)TPU/GPU fleet utilizationMLOps