Skip to content
Skip to content
AI Engineer Jobs
Google

Senior Software Engineer, Google Distributed Cloud AI

Google

Location
Onsite (Sunnyvale, CA)
Compensation
$174k - $252k/yr
Employment
Full-time
Level
Senior Level
Posted 1 day ago

About the Role

Join Google's Distributed Cloud AI team to lead the technical design and development of software components for Large Language Model inference. You will drive integration across core services and optimize serving capabilities for hybrid cloud and edge environments.

Skills

Software Development Distributed Systems Go AI/ML Large Language Models Kubernetes Cloud Computing System Design Infrastructure Networking Data Structures Algorithms Technical Leadership Container Orchestration Hardware Architecture

Benefits

  • Health Insurance
  • Bonus
  • Equity

Perks

  • Bonus
  • Equity

Full job details

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience with software development in one or more programming languages.
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  • 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
  • Experience programming in Go for software development, including AI/ML applications.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • 5 years of experience with data structures and algorithms.
  • 1 year of experience in a technical leadership role.
  • Experience with container orchestration (e.g., Kubernetes) and cloud-based AI platforms.

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.

Join our pioneering team dedicated to democratizing access to Google's AI solutions by integrating and developing them deeply within the Google Distributed Cloud (GDC) Platform. We are passionate about enabling customers to harness the power of AI, no matter their environment. Our work spans the full range of GDC offerings:

If you are excited about shaping the future of AI on the edge and in hybrid clouds, and addressing unique challenges across various deployment models, we want to hear from you!
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

  • Lead the technical design, development, and optimization of software components critical for Large Language Model (LLM) inference serving on GDC. This includes areas such as model life-cycle management, efficient data loading, dynamic request routing, and intelligent load balancing.
  • Drive horizontal integration across core platform services, including billing, logging, observability, security, and quota management.
  • Implement and enhance serving capabilities to support advanced LLM techniques like disaggregated serving, speculative decoding, quantization, and efficient model sharding across distributed hardware.
  • Collaborate closely with internal teams developing core LLM frameworks, container orchestration (Kubernetes, Google Kubernetes Engine (GKE)), networking infrastructure, and hardware acceleration to build a cohesive and high-performance serving platform.