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 |
|---|---|---|
| Machine Learning Hardware Architect, Hardware, Software Co-Design, Google Cloud This role focuses on architecting and defining the roadmap for AI/ML hardware acceleration, specifically TPUs, for Google Cloud. It involves co-design between model architecture and next-generation hardware, optimizing for ML serving and training capabilities, and integrating large-scale foundation models with advanced silicon architectures. The role requires defining technical roadmaps, architecting simulation frameworks, guiding system-level performance analysis, and managing cross-functional partnerships across hardware, compiler, and ML teams. | ServePost-train | 9 |
| Technical lead, Google Cloud Security Technical lead for Google Cloud Security, focusing on transitioning to an AI-native Security Operations Center (SOC). The role involves architecting an Agent Engine and universal APIs to enable enterprise security teams to orchestrate defense at machine speed, shifting from static workflows to multi-agent ecosystems. |
| Agent |
| 8 |
| Research Data Scientist II, Waze This role focuses on developing and owning Machine-Learning models for Waze's personalized navigation experience. Responsibilities include feature engineering, model evaluation, tuning, monitoring, and working with product and backend teams to integrate models into production. The role requires experience in data engineering, ML, and cloud platforms. | Post-train | 7 |
