Senior Staff Engineer, GDC AI Inference Platform
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- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience with software development, programming in C++, Java, Python, Kotlin, or Go.
- 5 years of experience testing, and launching software products.
- 4 years of experience in technical leadership (as a Tech Lead, Staff, or Principal Engineer) leading the architecture, design, and delivery of large-scale distributed systems or cloud infrastructure platforms.
- 3 years of experience with software design and architecture.
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.
- 5 years of experience in a technical leadership role leading project teams and setting technical direction.
- Experience designing orchestration platforms or runtime environments for Agentic AI, focusing on multi-agent coordination, state persistence, tool integration, and secure sandboxed execution.
- Deep expertise in ML systems engineering, including optimizing LLM serving architectures (e.g., disaggregated serving, speculative decoding, or high-throughput inference engines) and containerization technologies (Kubernetes, Docker).
About the job
Google Cloud’s mission is to make every business successful through AI by combining cutting-edge technology, infrastructure, and talent. AI/ML software engineers in Cloud bridge the gap between pioneering models and a massive product vehicle reaching billions. Our talent density and AI-powered tools drive rapid development, rooted in a culture of empowerment and a bias to action. In this role, you aren’t just building technology; you’re shaping the frontier of enterprise and driving the evolution of advanced models.
As a Senior Staff Software Engineer, you will architect the core infrastructure powering Google’s most advanced Large Language Models (LLM) and emerging Agentic AI capabilities. Within Google Distributed Cloud (GDC) AI, you will be the principal technical authority managing our next-generation global platform strategy. You will own ambiguous, massive-scale issues across LLM serving and agent orchestration, directly enabling performant, secure AI capabilities for our global enterprise customers.
In this executive-level technical leadership role, you will define the technical vision and roadmap for our high-performance inference stack, optimizing resource utilization and reliability. You will pioneer the frameworks, runtime environments, and tools necessary to support Agentic AI systems. This includes addressing multi-agent coordination, state management, tool integration, and secure, isolated execution environments.
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: $262000 - $365000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Define the GDC AI infrastructure roadmap for LLM serving and Agentic AI platforms, managing key architectural decisions, technology choices, and system health.
- Architect scalable, reliable LLM serving infrastructure, pioneering crucial optimizations like disaggregated serving to maximize resource and hardware efficiency.
- Build the core platforms and orchestration tools necessary for multi agent systems, seamless tool integration, state persistence, and secure, isolated execution environments.
- Collaborate with AI Research, Site Reliability Engineering (SRE), Product, and core platform teams to align and deliver integrated, production-ready AI solutions.
- Resolve ambiguous, high impact systems issues, balancing immediate enterprise customer needs with architectural integrity.
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