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 |
|---|---|---|
| Forward Deployed Engineer III, GCC (French, German) Google Cloud is seeking a Forward Deployed Engineer III to build and deploy agentic AI solutions for enterprise customers. This role involves bridging the gap between frontier AI products and production-grade reality, architecting and coding connective tissue, and building evaluation pipelines and observability frameworks. The engineer will also act as a product catalyst by identifying friction points and converting them into product feature requests. The role requires experience in designing and deploying NLP models and Generative AI agents, implementing MLOps pipelines, and building generative AI solutions in a customer-facing capacity. | AgentEval Gate | 9 |
| Forward Deployed Engineer, Generative AI, Google Cloud Consulting Forward Deployed Engineer for Generative AI on Google Cloud, focused on building and deploying bespoke agentic solutions within customer environments. This role bridges frontier AI products with production reality, addressing integration, data readiness, and state-management issues. Responsibilities include leading AI application development, architecting connective tissue between AI products and customer infrastructure, building evaluation pipelines and observability frameworks, identifying friction points for product feedback, and co-building with customer teams. |
| AgentEval Gate |
| 9 |
| Forward Deployed Engineer IV, Generative AI, Google Cloud Forward Deployed Engineer (FDE) at Google Cloud, embedding with customers to build and ship bespoke agentic AI solutions. This role involves coding, debugging, integrating AI products with customer infrastructure, and providing feedback to product teams. Focuses on production-grade agentic workflows, evaluation pipelines, and observability. | AgentServe | 9 |
| GECX AI Forward Deployed Engineer, Google Cloud Google Cloud is seeking an AI Forward Deployed Engineer to lead the development and productionization of conversational AI and agentic workflows for enterprise customers. This role involves transforming prototypes into scalable, secure AI systems, architecting conversational flows, building evaluation pipelines, and optimizing agent performance. The FDE will work closely with customers and internal engineering teams, leveraging Google's AI portfolio and Vertex AI platform. | AgentEval Gate | 8 |
| GECX AI Forward Deployed Engineer I, Google Cloud Forward Deployed Engineer (FDE) in Applied AI for Google Cloud, focused on transforming conversational AI prototypes into production-ready, end-to-end engineered solutions for enterprise customers. This role involves architecting and coding agentic workflows, building evaluation pipelines, and ensuring scalability and security of AI systems. | AgentServe | 8 |
| Google Cloud Consulting Forward Deployed Engineer, Generative AI, Google Cloud Google Cloud is hiring a Forward Deployed Engineer (FDE) specializing in Generative AI. This role involves embedding with customers to build and deploy bespoke agentic AI solutions, bridging the gap between frontier AI products and production realities. Responsibilities include developing agentic workflows, integrating AI products with customer infrastructure, building evaluation pipelines, and providing feedback to product teams. The role requires software development experience, cloud platform expertise, and experience with RAG and vector databases, with preferred experience in multi-agent systems and LLM optimization. | AgentEval Gate | 8 |
| Forward Deployed Engineer III, Generative AI, Google Cloud Forward Deployed Engineer III for Generative AI on Google Cloud, focused on building and shipping bespoke agentic solutions for enterprise customers. This role involves integrating Google's AI products (like Gemini and Vertex AI) into customer environments, addressing integration complexities, data readiness, and state management. Responsibilities include developing production-grade agentic workflows, architecting connective tissue between AI products and customer infrastructure, building evaluation pipelines and observability frameworks, identifying field patterns for product improvement, and co-building with customer teams. Requires strong software development skills (Python), experience with cloud AI systems, RAG, vector databases, and leading technical discovery. Preferred experience includes multi-agent systems and LLM-native metrics. | AgentEval Gate | 8 |
| Staff Engineering Analyst This role focuses on analyzing and mitigating AI-driven threats within Google's ad traffic quality systems. The individual will identify future misuse vectors, develop proactive mitigation plans, and lead initiatives to implement next-generation safety measures, including fine-tuning techniques and classifier-based guardrails. They will partner with engineering teams to improve ad traffic infrastructure and defense systems using advanced machine learning, and innovate methods to incorporate AI models for improving manual review operations and generating insights. | AgentPost-train | 7 |