Minimum qualifications:
- Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience.
- 8 years of experience architecting, building, and shipping distributed systems, particularly in a cloud environment.
- 8 years of experience with software development in one or more programming languages (e.g., Python, Go, Java, C++).
- 2 years of experience in applied Artificial Intelligence/Machine Learning (AI/ML), shipping production ML systems and building prototypes with Large Language Models (LLMs).
Preferred qualifications:
- Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Experience influencing the technical roadmap and strategy for an entire product area or organization.
- Experience in cost optimization, Financial Operations or building resource forecasting and recommendation systems.
- Experience in algorithms, data structures, and system design for high-throughput, low-latency services.
- Experience with one or more public cloud platforms.
- Knowledge of advanced AI techniques (e.g., Retrieval-Augmented Generation (RAG), Chain-of-Thought (CoT), ReAct, function calling, agentic frameworks) and their practical application in solving real-world problems.
About the job
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.
As a Staff Software Engineer on the Google Cloud Assist Optimize team, you will be a principal technical leader, setting the long-term goals for how we empower developers and engineers to manage costs on Google Cloud Platform (GCP) through AI. You will move beyond project-level execution to architect foundational systems, address the most ambiguous and technical issues, and multiply the impact of the entire engineering organization. This role requires a blend of technical expertise in AI and distributed systems, thinking, and the ability to influence and lead without direct authority. You will be instrumental in pioneering the future relationship between Platform Engineering and Financial Operations through AI, making Google Cloud the most cost-effective and intuitive platform for our customers.
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.
Responsibilities
- Drive the overarching technical strategy and architecture for the entire suite of AI-powered optimization agents.
- Design and prototype foundational frameworks and systems that enable multiple engineering teams to build, test, and deploy AI agents rapidly and reliably.
- Lead cross-team design and architecture reviews for the most critical systems, ensuring our technical direction is coherent, scalable, and mitigates long-term risk.
- Partner with executive leadership to define a multi-year technical roadmap. Translate the needs of Developers, Platform Engineers, and Financial Operations partners into a clear, actionable technical strategy.
- Solve the most testing, cross-cutting technical problems that span multiple systems or teams, often with no clear owner.
