Staff Software Engineer, Vertex Core Infra, Cloud AI

Socket.dev; Sunnyvale (CA); On-site; USD 210,000 - 300,000; Full time

Job summary

Google is seeking a senior software engineer to lead the infrastructure for Vertex AI products in the United States. You will solve backend bottlenecks, ensure security and compliance, and collaborate with multiple AI initiatives to integrate Vertex AI across platforms.

You will build scalable foundations for enterprise-grade AI services, guiding systems to handle growth and reside across multiple regions with resilience.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• Experience integrating generative AI tools or Large Language Model (LLM) interfaces into workflows.
• Experience with Kubernetes, C++, and Go programming.
• Experience working with Apps Framework, Distributed Systems, Spanner, Google Cloud Platform, One Platform, and Compliance.

Responsibilities

• Lead, design and implement business critical Infra for Vertex AI products. Solve complex backend system problems to address bottlenecks for system scalability and reliability, adapting the system to rapid business growth.
• Drive implementation to make Cloud AI products meet security and compliance requirements in order to unblock customers in certain industries (e.g., financial industry, healthcare).
• Work closely with other AI initiatives within Google, including Gemini serving, Partner MaaS, Agents.
• Build Vertex AI into the full lifecycle of customer's machine learning workflows by improving interoperability within multiple Vertex AI products and with other GCP/non-GCP services (e.g., Kaggle, HuggingFace, TFHub).
• Learn and apply emerging AI infrastructure patterns (e.g., model lifecycle automation) to build a foundation for Vertex AI.

Skills

Software design and architecture

Software testing

Generative AI integration

LLM workflow integration

Education

Bachelor’s degree or equivalent practical experience

8 years of experience in software development

Tools

Kubernetes

C++

Go

Apps Framework

Distributed Systems

Spanner

Google Cloud Platform

One Platform

Compute Engine

IAM

GKE

CMEK

Wipeout

Compliance

Job description

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• Experience integrating generative AI tools or Large Language Model (LLM) interfaces into workflows.
• Experience with Kubernetes, C++, and Go programming.
• Experience working with Apps Framework, Distributed Systems, Spanner, Google Cloud Platform, One Platform, and Compliance.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 8 years of experience with data structures and algorithms.
• 3 years of experience with distributed system design of infrastructure software.
• Experience building or operating large-scale services on Google Cloud Platform (GCP), specifically leveraging technologies like Spanner, IAM, OnePlatform, GKE, or Compute Engine, and familiar with Compliance requirements such as CMEK and Wipeout.
• Track record of solving ambiguous infrastructure problems, such as system performance bottlenecks or multi-region availability.
• Motivated Tech Lead (TL) who is passionate about building reliable, scalable foundation infrastructures that powers many AI products.

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.

Build infrastructure that powers many Vertex AI products and solutions, including Gen AI, Agent, Document AI, Vision AI, etc. Build foundational infrastructure to make Vertex AI more enterprise ready by providing reliable and scalable infrastructure, and advanced security and compliance features (e.g. access control, auth, security horizontals).

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: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

• Lead, design and implement business critical Infra for Vertex AI products. Solve complex backend system problems to address bottlenecks for system scalability and reliability, adapting the system to rapid business growth.
• Drive implementation to make Cloud AI products meet security and compliance requirements in order to unblock customers in certain industries (e.g., financial industry, healthcare).
• Work closely with other AI initiatives within Google, including Gemini serving, Partner MaaS, Agents.
  
• Build Vertex AI into the full lifecycle of customer's machine learning workflows by improving interoperability within multiple Vertex AI products and with other GCP/non-GCP services (e.g., Kaggle, HuggingFace, TFHub).
• Learn and apply emerging AI infrastructure patterns (e.g., model lifecycle automation) to build a foundation for Vertex AI.