About the role
What will you do at Google?
MINIMUM QUALIFICATIONS:
* Bachelor’s degree or equivalent practical experience.
* 8 years of experience architecting, implementing, and operating large-scale
distributed systems, transactional storage engines, or high-performance
database internals.
* 5 years of experience with ML design and ML infrastructure (e.g., model
deployment, model evaluation, data processing, debugging, fine tuning).
* 5 years of experience developing production-critical systems in Rust.
* 3 years of experience in technical leadership, setting multi-year
architectural roadmaps, and driving cross-organizational technical
initiatives.
* Experience with formal specification, formal methods, or verified systems
development (e.g., Verus, TLA+, SMT verification, or proof-carrying code).
PREFERRED QUALIFICATIONS:
* PhD in Computer Science with a focus on Distributed Systems, Transactional
Storage, Database Engines, or Formal Verification.
* Track record of architecting petabyte-scale storage engines, distributed
consensus protocols or low-latency key-value databases.
* Expertise in hardware-conscious algorithmic design, query optimization,
LSM-tree architectures, and zero-copy memory pipelines.
* Contributions to the broader systems and Rust open-source ecosystems (e.g.,
authoring/maintaining widely adopted crates, database engines, or storage
primitives).
* Ability to influence executive leadership and drive adoption of
transformative security and verification technologies across multiple product
areas.
* Research publications in systems and data engineering venues (e.g., OSDI,
SOSP, NSDI, VLDB, SIGCOMM, EuroSys).
ABOUT THE JOB:
Google Cloud's software engineers develop the next-generation technologies that
change how billions of users connect, explore, and interact with information and
one another. 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 Cloud's needs with opportunities to switch teams and projects as you and
our fast-paced business grow and evolve. You will anticipate our customer needs
and be empowered to act like an owner, take action and innovate. 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.
Individual pay is determined by factors including job-related skills,
experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google
[https://www.google.com/about/careers/applications/benefits/].
RESPONSIBILITIES:
* Lead the design and implementation of solutions in specialized ML areas,
optimize ML infrastructure, and guide the development of model optimization
and data processing strategies.
* Define the multi-year technical vision and architectural roadmap for
high-efficiency, formally verified systems across Google Cloud CISO.
* Lead the end-to-end architecture and implementation of distributed
transactional systems, storage layers, and query engines built in Rust and
verified with Verus. Formulate verification strategies for complex,
multi-component distributed protocols, proving correctness, fault tolerance,
and data integrity under arbitrary failure modes.
* Lead initiatives to replace bug-prone, resource-heavy legacy components with
formally verified, resource-efficient alternatives across internal and
open-source infrastructure. Partner with VP-level and Principal engineering
leadership to establish organization-wide verification standards, security
baselines, and developer tooling.
Which skills does this role require?
Make your next move
Build a shortlist and prepare
Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.
- Build a focused shortlist before you applyCompare role requirements with your experience and give each application a clear reason.
- Practice explaining your experience in an interviewRehearse your answers before meeting the hiring team.
Other roles to compare
Review the responsibilities and requirements before adding an opening to your shortlist.
AI Outcome Customer Engineer, Forward Deployed Engineering
Google · Atlanta, Georgia, United States
Orchestration Workload Engineer - ACE - AI Factory
Roche · Kaiseraugst, Aargau, Switzerland
Data Analyst ServiceNow Developer
SiloSmashers, Inc. · District of Columbia, United States
AI Solutions Engineer
Vantage Bank · Fort Worth, Texas, United States
Principal Engineer, Content and Generative AI Exploration, Search Platforms
Google · Mountain View, California, United States
AI Evaluations Engineer, US Decision Intelligence
Apple · Cupertino, California, United States
Role information can change. Confirm current details on the original application page.
