About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

Rust is a modern programming language for building memory safe software that can match C++ in performance and resource efficiency. It's a critical component of Google's long-term vision to increase adoption of memory safe languages across the company.

This is an ambitious initiative, now supported by the Core Innovation Fund. RustShift accelerates Google’s migration to Rust by leveraging AI to automate the translation of C/C++ codebases. As a member of RustShift, you will be contributing to a critical foundation for Google’s future, ensuring that we can scale memory safety rapidly and efficiently while maintaining the performance, reliability, and usability our products demand.

We empower Googlers to be productive by providing developer tools, services, and support for the languages that underpin Google's core products and services.

Responsibilities

• Develop and refine agentic workflows that automate the large-scale migration of C/C++ codebases to idiomatic, memory-safe Rust.
• Collaborate with the wider Rust team on C++/Rust interop, developer tooling, and AI benchmarks. Design multi-agent harnesses for automated code translation, self-review, verification, and performance analysis.
• Design strategies for evaluating the output quality of agentic code generation, automatically distilling eval examples where the tooling fails today, and fixing quality problems. Implement advanced verification workflows, including differential fuzzing and formal verification, to guarantee bit-identical behavior with legacy 3P C/C++ libraries.
• Optimize AI-generated Rust code for performance and resource efficiency, leveraging benchmarks to guide translation, then level-up these optimizations into the tooling.
• Collaborate with key teams and individuals in the AI and programming language spaces to evolve our translation tooling, and incorporate the latest techniques.