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.
Currently tracking 498 active AI roles, down 12% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $98k–$1030k (avg $233k).
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 |
|---|---|---|
| Research Engineer, Frontier Safety Mitigations, DeepMind Research Engineer focused on frontier AI safety mitigations, defending against misuse domains like CBRNE and Harmful Manipulation. Responsibilities include building evaluations, red-teaming, deploying in-model and out-of-model mitigations, and monitoring risks for frontier models, particularly agentic AI systems. The role involves developing classifiers, monitoring systems, and advancing research in automated red-teaming and adversarial robustness. | AgentEval Gate | 9 |
| Research Engineer, Multi Agent Learning, DeepMind Research Engineer at Google DeepMind focused on developing novel multi-agent learning algorithms and frameworks. The role involves building and maintaining large-scale simulation platforms and research pipelines on cutting-edge infrastructure, partnering with Research Scientists to translate research into production-quality code, and optimizing the research workflow. Requires experience in deep learning frameworks, Python/C++, and distributed training on accelerators. A PhD in ML, RL, or Multi-Agent Systems and experience with language models are preferred. |
| AgentPost-train |
| 9 |