Senior AI Developer Productivity Engineer
Zoox · Foster City, CA
Skills in this posting
The posting
Zoox is developing state-of-the-art autonomous vehicle software for our purpose-built vehicle. We believe that developing the end-to-end product will get us to market faster and result in a superior customer experience.
The Developer Experience team at Zoox is dedicated to improving the process of developing autonomy software, services, and applications. We define and enforce the best practices for engineering across the company. Our approach involves using established programming languages, and tools and, when necessary, developing our own.
We're leveraging Large Language Models (LLMs) to improve development velocity and streamline engineering workflows. We're looking for an engineer with firsthand experience as a full-stack developer, who knows the engineering challenges at scale and feels comfortable designing and implementing solutions to address them.
In this role, you will
Architect and implement LLM-powered solutions using frontier models like Claude, Gemini, GPT.
Build tools that leverage AI and improve engineer productivity by 10x through intelligent code assistance, automated code review, and improving zoox’s operational efficiency.
Develop systems to automate mundane development tasks like boilerplate generation, test creation, and code refactoring.
Create intelligent workflows that leverage LLMs for bug detection, security vulnerability assessment, and code optimization.
Bridge the divide between developers' needs and infrastructure solutions while establishing best practices for responsible AI integration in our development pipeline.
Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, or a related field with 7+ years of industry experience.
Solid experience as a full-stack or backend developer, showcasing a deep understanding of system design, data structures, and algorithms.
Fluency in at least one of the following languages: Python or C++.
Experience with LLM evaluation metrics and performance optimization
Knowledge of using embedding models and vector databases
Bonus Qualifications
Experience working with IDEs and LSPs
Experience developing and/or integrating debuggers with build systems
Experience managing and optimizing large monolithic repositories, including build systems, version control workflows, and developer tooling
The PivotHop read
- What an ai engineer actually earnsmedian, seniority, by country
- AI Engineer career changes, measuredevery measured route out
- Machine Learning Engineer → AI Engineer59% readiness
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Where these skills also reach
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