Currently tracking 498 active AI roles, down 12% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $98k–$1030k (avg $233k).
Google has 584 active AI-related job listings. The majority of these roles are focused on agents, representing 40% of the total, and serving infrastructure, at 26%. The most frequent technical tags include model_serving, agent_orchestration, and evals. Over the last 30 days, Google has added 413 new AI roles, a 105% increase compared to the preceding 30-day period.
Google currently has 586 active AI-related roles in our index. The most common open titles are: Software Engineer (5), AI Adoption Customer Engineer, Google Cloud (3), Conversational AI Consultant (2), Engineering Manager, Egregious Abuse Protection (2), Forward Deployed Engineer III, Generative AI, Google Cloud (2). Most positions are in Engineering and Product.
Google's active AI hiring is concentrated in: agents (43%), serving infrastructure (25%), application (19%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Google is hiring AI talent in: United States (376 roles), India (53 roles), Singapore (40 roles), Switzerland (20 roles).
Job postings at Google most frequently mention: Software Engineering, Algorithms & Data Structures, System Design, Computer Architecture, Machine Learning.
In the past 30 days, Google has posted 571 new AI-related roles. That is a +22% change versus the prior 30 days (469 → 571).
| Title | Stage | AI score |
|---|---|---|
| Senior Product Manager, AI Garage Senior Product Manager for AI Garage at Google, focusing on defining and delivering AI-powered agentic products for HR processes. The role involves shaping AI-native product strategy, writing PRDs for systems with non-deterministic behavior (including fine-tuning and RAG), partnering with researchers on model requirements, pioneering multi-agent execution frameworks, and implementing LLM evaluation systems. Requires deep technical fluency in generative AI and experience launching technical products. | AgentPost-train | 9 |
| Product Manager, Workspace Search Product Manager for Workspace Search, focusing on improving search quality for human users and enabling agentic users to retrieve and utilize Workspace data. This role involves defining intelligent systems, developing APIs for agents, and driving the strategy for automated evaluation frameworks, working at the intersection of Search and AI. |
| AgentServe |
| 8 |
| Product Manager, AI Garage Product Manager for Google's AI Garage, focusing on applying AI and agentic workflows to solve HR challenges for Google's global workforce. The role involves driving the product lifecycle from ideation to launch, collaborating with AI/ML engineers and data scientists, and translating user needs into product requirements. | Agent | 7 |
| Product Manager, Geo User-Generated Content Trust Product Manager for Google Geo User-Generated Content Trust, focusing on leveraging AI/ML models to reduce fraud and abuse in Google Maps UGC. This role involves defining product strategy, roadmaps, and success metrics, and collaborating with engineering, analytics, and other cross-functional teams. | Ship | 7 |
| Senior Product Manager, Applied AI, Google Cloud Senior Product Manager for Applied AI within Google Cloud, focusing on enterprise-grade products like Healthcare APIs and Risk AI models. The role involves defining strategy, roadmaps, and features for AI/ML products, collaborating with data science teams on model quality, and managing relationships with global banks and healthcare organizations. Requires experience in launching AI/ML products, particularly in Generative AI and large models, with a focus on balancing model quality and cost. | Ship | 7 |
| Technical Program Manager, Google Cloud Applied AI This role is for a Technical Program Manager focused on building high-impact AI agents for enterprise clients within Google Cloud. The TPM will elicit business requirements, conduct A/B testing and PoCs, collaborate with Data Science and Engineering on data pipelines for ML models, and ensure solutions address supply chain bottlenecks. They will also manage a team of TPMs, including resource allocation and hiring. The role involves integrating generative AI solutions into business processes and agent-based modeling. | Agent | 7 |