Staff Software Engineer, Applied AI Engineering

Job description

Architect secure, highly cost-effective distributed systems and MLOps pipelines on Google Cloud Platform (GCP) for fine-tuning and serving frontier models. Translate AI/ML research into production-grade services, optimizing model inference latency, throughput, and large-scale TPU/GPU fleet utilization. Design robust, self-improving multi-agent architectures and cognitive planning engines capable of executing complex, guardrailed workflows. Shape Google Cloud’s AI roadmap by feeding operational insights and technical gaps from incubation projects directly back to core engineering. Mentor executive engineers across teams, driving a culture of rapid prototyping, rigorous system design, and technical excellence. Minimum Qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture. 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). 2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision). Preferred Qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field. Experience building advanced GenAI (multi-step LLM, multi-agent systems, or model context protocol (MCP) integrated with orchestration frameworks). Working knowledge of leverage AI/ML, automation, and advanced technologies to optimize workflows and enhance efficiency. Demonstrated ability to lead and deliver on complex, ambiguous projects. Excellent problem-solving, investigative, and technical leadership skills.