Senior Staff Engineer, Agentic AI Engineering
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Apply to this jobWaymo 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.
Waymo's core business scale is bottlenecked by improving long tail behaviors. The growth in vehicles, platforms, geos (e.g. international), and ODD (e.g. weather) creates a huge set of new problems that we have to solve quickly. The methodical process of building driving sets and high quality metrics cannot scale to Waymo's upcoming needs. We are looking for a senior IC to redefine the way we hillclimb and build eval to scale the Waymo driver.
In this hybrid role, you will report to an Engineering Director.
You will:
- Design, build, and deploy production-grade agentic AI systems to solve complex, open-ended evaluation challenges.
- Develop robust, automated evaluation frameworks and objective metrics to continuously measure the accuracy, safety, and reliability of non-deterministic AI agents.
- Automate the building and scaling of the hardest eval problem inhibiting Waymo's scale.
You have:
- Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
- Proven technical leader with a track record of designing, building, evaluating, and deploying novel agent-based AI solutions into production
- Deep expertise in Artificial Intelligence and Machine Learning, with heavy, hands-on experience building autonomous agents, multi-agent orchestration systems, and integrating LLMs with external tools/APIs.
- Extensive experience (typically 7+ years) in software engineering, with a significant focus on architecting and building large-scale, complex systems.
- Proven ability to define technical strategy, influence senior leadership, and drive execution across multiple teams in ambiguous and rapidly evolving domains.
- Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to diverse audiences.
We prefer:
- PhD in Computer Science or a related field, with a specialization in AI/ML or a related area.
- Experience with agentic frameworks, knowledge graphs, and reasoning engines.
Proficiency in C++ and experience with building production-grade services. - Familiarity with autonomous vehicle simulation, testing, or evaluation domains.
- 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 the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Compensation (from employer):
Salary Range — 251,000 – 310,000 USD
Summary
Design and deploy AI systems for evaluation and scaling of autonomous driving agents.
Job title
Senior Staff Engineer, Agentic AI Engineering
Experience level
7+ years
Minimum experience
7+ years exp
Industry
software
Location requirements
Hybrid role in California, remote possible
Salary
$251k–$310k
Visa sponsorship
H-1B sponsor history
Management role
No
Required skills
Preferred skills
Specializations
Structured locations inferred from the posting.
Mountain View, CA, USA
San Francisco, CA, USA