Senior Staff Software Engineer, Cloud AI, Agent Governance

Google Inc.; Sunnyvale (CA); On-site; USD 262,000 - 364,000; Full time

Job summary

Google is seeking a Senior Staff Software Engineer for Cloud AI, Agent Governance in Sunnyvale, CA to architect and deliver scalable ML infrastructure and governance for enterprise deployments.

You will own outcomes, lead architecture across teams, design evaluation systems, and build tooling for agentic workflows, tool calls, and multi-turn simulations.

This role requires deep expertise in GenAI, distributed systems, and strong collaboration with product and research teams.

Qualifications

• 8 years of software development experience.
• 7 years leading technical strategy, ML design, and ML infra optimization.
• 5 years in design/architecture, testing and launching software products.
• 2 years experience with GenAI techniques or related concepts.

Responsibilities

• Architect, build, and operate large-scale ML environments for agent governance.
• Deliver evaluation infrastructure and test harnesses with enterprise visibility and security.
• Design scalable platform infrastructure for agentic systems and audit trails.
• Build metrics engines and dashboards for evaluation coverage and quality.
• Integrate evaluation runs into deployment pipelines and release gates.

Skills

Outcomes ownership

Decision making

ML design

Architectural design

GenAI techniques

LLM tool-calling

Telemetry at scale

Enterprise-grade platforms

Education

Bachelor's degree or equivalent practical experience

Tools

Large-scale ML infrastructure

Sandbox environments

Evaluation tooling

Job description

Senior Staff Software Engineer, Cloud AI, Agent Governance

corporate_fare Google place Sunnyvale, CA, USA

Advanced

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders;deep expertise in domain.

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 7 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with design and architecture, and testing, launching software products.
• 2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

Preferred qualifications:

• 10 years of experience leading the design and implementation of scalable distributed systems, ML platforms, or observability infrastructure, ideally in the context of large-scale agent platforms.
• Experience leading engineering teams and collaborating with product managers and researchers to translate scientific concepts into reliable developer tools.
• Strong understanding of LLM execution mechanics, tool-calling APIs, and model-level failure analysis.
• Fluency in distributed tracing, semantic monitoring, and telemetry collection at scale.
• Proven track record of shipping complex enterprise-grade developer platforms, virtualization/sandbox environments, or production-grade test harnesses.

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.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

Google Cloud is building the most comprehensive AI platform in the industry. As platform adoption scales, enterprise customers require stable, highly scalable, and completely secure simulation environments and evaluation infrastructure to operationalize autonomous agents. This role focuses on the systems and platform engineering required to close the last mile of agentic governance for enterprise deployments.

You will lead the delivery of the engineering roadmap, integrating components from multiple product teams to build an intuitive governance user experience for CISOs, auditors, and enterprise IT teams. The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud's mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real‑world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google .

• Architect, build, and operate large-scale environments that allow developers to test complex agent behaviors, tool calling, multi-turn workflows, and end-to-end workflows in isolated, reproducible sandboxes.
• Deliver reproducible evaluation infrastructure and automated test harnesses capable of validating against enteprise visibility, security, compliance requirements.
• Design and scale the platform infrastructure that enables agentic systems to validate online and audit offline and alert based on behavioral patterns.
• Build the metrics engines and dashboards to track evaluation coverage, semantic correctness, quality metrics, and regression signals over time. Standardize the use of metrics for production health.
• Integrate evaluation runs into deployment pipelines, creating release gates to prevent semantic and structural regressions before agent deployments reach production.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.