Director of Engineering, DevAI

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.

Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers.

If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you.

You will report to our Head of Onboard Engineering.

• Define and drive the technical vision and roadmap for AI-powered developer tools and agent development across Waymo by partnering closely with engineering teams across Waymo to understand their workflows, identify high-impact opportunities, and drive the adoption of new DevAI tools. Interface across Alphabet companies to craft a joint strategy that leverages technology at the forefront of the industry to address Waymo's unique needs.
• Spearhead the design, development, and deployment of novel AI agents and tools to address Waymo's unique engineering challenges. This includes but is not limited to:
  • Advanced, context-aware code generation, completion, and refactoring.
  • Intelligent systems to accelerate the troubleshooting of complex driving behaviors observed in the real world and in simulation.
  • AI-powered assistance for event triage, root cause analysis, and bug fixing.
  • Tools to enhance the efficiency and quality of data labeling and curation.
  • Smart agents to optimize and augment simulation and testing workflows.
• Develop models that excel on Waymo's unique requirements and enable these agentic use-cases by leveraging Google's and Waymo's cutting-edge foundational models. Develop data pipelines, training strategies, and eval approaches to product ionize these models.
• Lead, mentor, and grow a team of talented software engineers, fostering a culture of innovation, rapid prototyping, and engineering excellence.
• Stay at the forefront of AI research, particularly in large language models (LLMs) and generative AI, and identify opportunities to apply these advancements to solve Waymo's challenges. Evaluate and integrate state-of-the-art agentic solutions and platforms.

• Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
• 12+ years of experience in software engineering, with a proven track record of technical leadership in architecting and delivering complex, large-scale systems.
• 8+ years experience leading and mentoring software engineering teams.
• Demonstrated expertise in machine learning, natural language processing, and/or generative AI, including hands-on experience developing and tuning LLMs.
• Understanding of software development life cycles, developer workflows, and tools.

• Master's or PhD in Computer Science or a related technical field, with a focus on AI/ML.
• Experience developing or applying AI-powered tools for software engineering.
• Deep understanding of modern AI architectures and techniques, including prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).
• A strategic mindset with the ability to translate high-level vision into a concrete and actionable roadmap.
• Experience designing, building, and deploying agentic AI systems and frameworks, including multi-agent systems and their application to complex problem domains.
• Except…