About the role
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation (DUE) team at Waymo is developing rich metrics for understanding the behavior of the Waymo Driver in the real world, and technologies such as context and scene analysis to understand driving, understanding and augmenting real world driving data to generate rare driving events, build large scale data infrastructure, improve components such as agents and a realistic simulator. These technologies come together to drive the overall technical strategy and methodology used to evaluate the behavior of the Waymo Driver. You will: Own the architectural design and hands-on development of robust Agentic AI components, focusing on multi-agent orchestration, tool execution, and reasoning loops for event triage. Engineer scalable agentic workflows using modern LLM orchestration frameworks to automate and augment triage capabilities for Engineering and SWQOps. Implement stateful agentic infrastructure, including long-term memory management (RAG, vector databases), semantic routing, and custom internal tool integrations. Collaborate with partner teams to embed autonomous agents directly into the Waymo Driver evaluation lifecycle. Tackle complex automation problems by breaking them down into actionable multi-agent projects and driving the technical execution of
the team's roadmap. You have: Significant experience (typically 5+ years) in software engineering, with a focus on designing, building, and maintaining complex distributed systems. Strong expertise in applied LLMs and Agentic AI development, with a proven track record of building multi-agent systems, reasoning engines, or autonomous workflows. Strong proficiency with agent orchestration frameworks and advanced prompt engineering. Proven ability to execute on technical strategy, collaborate inclusively with cross-functional teams, and drive end-to-end development of AI-native applications. Excellent communication skills, with the ability to clarify technical limitations and solutions for partner teams. Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience. We prefer: Master's or PhD in Computer Science or a related field, with a specialization in AI/ML or a related area. Experience developing custom tools/plugins for agents, semantic routers, and implementing complex multi-agent collaborative patterns. Familiarity with autonomous vehicle simulation, testing, or evaluation domains. Proficiency in C++ and Python, with experience building production-grade microservices and pipelines. Experience working with large-scale data processing, knowledge graphs, and distributed systems. Familiarity with Google's or Waymo's internal AI/ML platforms and infrastructure. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for