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 |
|---|---|---|
| Forward Deployed Engineer II, GCC Forward Deployed Engineer II, GCC role focused on embedding with customers to build, deploy, and productionize bespoke agentic AI solutions using Google Cloud's AI portfolio. Responsibilities include architecting integrations, developing agentic workflows, building evaluation and observability pipelines, and providing feedback to product teams. Requires experience in software development, ML, NLP, generative AI agents, and DevOps, with preferred experience in multi-agent systems and LLM optimization. | AgentEval Gate | 9 |
| Software Engineer lll, AI Developer Tools Platform Software Engineer III on the AI Developer Tools Platform team, focusing on integrating Generative AI and LLMs for Cloud customers. Responsibilities include designing and implementing the platform, collaborating with researchers and product managers, and managing project priorities. Requires experience with ML infrastructure and software development. |
| ServeAgent |
| 8 |
| Software Engineer III, Vertex Inference Software Engineer III for Google Cloud's Vertex Inference team, focusing on the dataplane for serving first-party models like Gemini. The role involves implementing GenAI solutions, utilizing ML infrastructure, and optimizing performance for AI/ML capabilities within Google Cloud. | ServePost-train | 8 |
| Software Engineer, GKE, PhD, Early Careers Google Cloud is seeking a Software Engineer to work on workload orchestration, specifically implementing a Cognitive Architecture where AI agents act as 'Principal Engineers' to write, validate, and deploy deterministic orchestration code. This role focuses on optimizing infrastructure for GenAI inference and improving resource utilization using AI. | AgentServe | 8 |
| Software Engineering Manager, Android Automotive AI/ML Software Engineering Manager for Android Automotive AI/ML, responsible for leading teams, setting technical direction, and shipping on-device ML products in the automotive domain. Focuses on integrating Google's AI technologies into vehicles. | Ship | 7 |
| Software Engineer II, Google Cloud Platform, Infrastructure Software Engineer II for Google Cloud Platform, focusing on the Kueue project, a CNCF open-source scheduler for AI workloads on Kubernetes. The role involves designing and building sophisticated scheduling solutions for accelerators (TPUs, GPUs) and large-scale CPU workloads, with a focus on algorithm design, system performance, and Kubernetes internals. The team also pioneers the use of Agentic AI for code development and issue diagnosis. | Serve | 7 |
| Senior Software Engineering Manager, Flume ML Senior Software Engineering Manager for Google Cloud's Flume ML team, focusing on leading a team to enhance a data processing infrastructure product. The role involves advancing scheduleability and auto-tuning capabilities for ML pipelines and standard data workloads, bridging infrastructure and products, and collaborating with teams on autonomous driving and frontier AI. | Serve | 7 |
| Engineering Manager, Hybrid and On-prem AI Infrastructure Engineering Manager for Hybrid and On-prem AI Infrastructure, focusing on building a novel on-premises AI supercomputer. The role involves technical leadership, team management, defining architecture and roadmaps, and collaborating with product and GTM leaders to deliver AI hardware and software solutions for customers with specific security and locality needs. | Serve | 7 |
| Staff Software Engineer, Vector Search, Vertex AI Staff Software Engineer role focused on Vector Search Serving infrastructure within Google Cloud's Vertex AI platform, supporting enterprise AI initiatives and Gemini models. Requires extensive experience in software development, distributed systems, and infrastructure, with a preference for GenAI techniques. | ServeAgent | 7 |
| Staff Full Stack Software Engineer, GKE Agentic Experience Staff Full Stack Software Engineer on the GKE Agentic Experience team, responsible for leading the design, development, and deployment of full-stack applications and services that leverage large language models and agentic systems to simplify cluster management, enhance feature discovery, and automate complex tasks within the Google Kubernetes Engine (GKE) ecosystem. The role involves contributing to technical strategy, mentoring engineers, and collaborating across teams. | Agent | 7 |
| Senior Software Engineer, AI/ML Infrastructure Senior Software Engineer focused on optimizing AI/ML infrastructure performance across the technical stack, from networking and data storage to ML models, to provide AI developers with a high-performance experience on Google's AI infrastructure. Responsibilities include designing and implementing solutions, optimizing performance, profiling, debugging, and developing tools for AI/ML infrastructure. | ServeData | 7 |
| Software Engineer, Early Careers, PhD, Cloud AI Software Engineer role focused on implementing and designing Search features, leveraging advanced GenAI capabilities and LLM concepts, with a focus on Kubernetes-based infrastructure for scalability and performance. | Serve | 7 |