Director of Engineering, DevAI

Software Engineering buildsthe brains ofWaymo'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.

You will:

• 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 productionize 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.

You have:

• 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 lifecycles, developer workflows, and tools.

We prefer:

• 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.
• Exceptional communication and interpersonal skills, with the ability to influence and collaborate with stakeholders at all levels, from individual contributors to senior executives.
• Experience in robotics, autonomous vehicles, or safety-critical systems.
• Passion for improving developer experiences, and a vision for the future of AI-assisted software development.
• Expertise in data engineering, including data cleaning, ingestion, and processing for large-scale ML model training, particularly with code and other domain-specific datasets.
• A background in Developer Productivity, including experience with code analysis, static analysis, and building internal developer platforms.
• Experience leading successful advocacy and training programs to drive the adoption of new technologies within a large engineering organization.