Staff Software Engineer, Emerging On-prem AI Infrastructure
Company: Google
Location: Cupertino
Posted on: January 9, 2026
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Job Description:
Minimum qualifications: Bachelors degree or equivalent practical
experience. 8 years of experience programming in C++. 5 years of
experience testing, and launching software products. 5 years of
experience building and developing large-scale infrastructure,
distributed systems or networks, or experience with compute
technologies, storage, or hardware architecture. 3 years of
experience with software design and architecture. Preferred
qualifications: Experience building cloud or systems level
infrastructure spanning the entire hardware and software stack.
Experience in end-to-end diagnostics, troubleshooting, and
supportability, with experience leading SWAT team efforts for
complex issues and developing long term sustainable solutions.
Familiarity with Service Level Objectives (SLOs)/metrics
measurement, logs/telemetry/metrics integration with tools for
enhanced operator experience. Understanding of low-level system
software, OS, firmware, low level networking, or hardware, etc.,
with a passion for building system skills. Ability to work in a
changing environment and navigate ambiguity, and a track record of
delivering solutions for subtle or complex technical problems.
About the job Googles 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. Were 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. In this role,
you will have exposure to integrated AI infrastructure systems (GPU
or TPU), from software to hardware design and workload management,
to developing large scale training and inference workloads, and
optimizing performance. You will be building large AI clusters
using the latest technologies for AI acceleration and cluster
interconnects and networking. The ML, Systems, & Cloud AI (MSCA)
organization at Google designs, implements, and manages the
hardware, software, machine learning, and systems infrastructure
for all Google services (Search, YouTube, etc.) and Google Cloud.
Our end users are Googlers, Cloud customers and the billions of
people who use Google services around the world. We prioritize
security, efficiency, and reliability across everything we do -
from developing our latest TPUs to running a global network, while
driving towards shaping the future of hyperscale computing. Our
global impact spans software and hardware, including Google Cloud’s
Vertex AI, the leading AI platform for bringing Gemini models to
enterprise customers. The US base salary range for this full-time
position is $197,000-$291,000 bonus equity benefits. Our salary
ranges are determined by role, level, and location. Within the
range, individual pay is determined by work location and additional
factors, including job-related skills, experience, and relevant
education or training. Your recruiter can share more about the
specific salary range for your preferred location during the hiring
process. Please note that the compensation details listed in US
role postings reflect the base salary only, and do not include
bonus, equity, or benefits. Learn more about benefits at Google .
Responsibilities Drive project success by setting the technical
goal and roadmap. Set priorities and projects for a team that
delivers features in a fast-moving environment for both internal
customers (other engineering teams) and external customers. Ensure
central responsibility is taken for diagnostics and troubleshooting
of end-to-end supportability issues, to uncover and address complex
technical problems, and the building of repair automation systems.
Implement and govern the success metrics for the team, spanning
Operational Plane metrics (e.g., Support case metrics, GSO case
handling), and RMA/Spares metrics (e.g., swap and repair rate).
Keywords: Google, Sunnyvale , Staff Software Engineer, Emerging On-prem AI Infrastructure, IT / Software / Systems , Cupertino, California