Group Product Manager, AI FinOps and Model Routing
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 10 years of experience in product management or a related technical role.
- 5 years of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc).
- Experience with API gateways, cloud networking, distributed proxy architectures, API management (APIM), or enterprise observability/telemetry platforms.
- Experience with Generative AI architectures and LLM APIs, tokenization mechanics, semantic caching, prompt chaining, reasoning loops, and multi-agent frameworks.
Preferred qualifications:
- Master's degree in a technology or business related field.
- 7 years of experience working cross-functionally with engineering, UX/UI, sales finance, and other stakeholders.
- 7 years of experience in a business function or role (e.g., strategic marketing, business operations, consulting).
- Experience in FinOps and cost governance: track record of building chargeback/showback mechanisms, quota management systems, or cost-optimization products for enterprise infrastructure.
- Knowledge of Envoy, WebAssembly (Wasm) extensions, Kubernetes Gateway API, or open-source AI proxy layers.
- Proven ability to align engineering, research, sales engineering, legal, and executive leadership behind ambitious multi-year roadmaps.
About the job
At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.
In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.
One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.
At Google Cloud, we are committed to being open to any model and any agent. We are building an AI Model Routing and Token Management Gateway, giving enterprises a single source of truth to observe, attribute, and enforce granular policies across their entire hybrid AI footprint. From sub-millisecond dynamic routing that matches prompt complexity with the optimal cost/performance engine, to cross-provider failovers that eliminate downtime, our platform provides the enterprise control plane for the generative AI era.
In this role, you will lead the end-to-end product goal, strategy, and execution for Google Cloud's Token Management and Intelligent Model Routing platform. You will bridge deep networking frontiers (e.g., Service Extensions, Envoy proxies, low-latency traffic management) with LLM runtime intelligence.
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: $240000 - $333000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Establish a bi-modal product strategy that serves application developers (integrations with AI Studio, Firebase, and open-source frameworks) while meeting the rigorous Financial Operations (FinOps), compliance, and multi-tenant demands of large enterprises.
- Drive market positioning and competitive differentiation against point solutions and hyperscaler native gateways.
- Lead methodology and standards for auto-router benchmarking, agentic evaluation datasets, and real-time routing optimization.
- Analyze multi-objective routing strategies, continuously optimizing across the Pareto frontier of cost, latency, contextual quality, and model family availability.
- Define strategy for agentic workload optimizations, planning loops, multi-turn tool calling, and agentic harnesses, and identifying and capitalizing on specific opportunities for intelligent routing within agentic graphs, such as intent classification, step-level model selection, context summarization routing, and verification loops.
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