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 |
|---|---|---|
| Staff Software Engineer, BigQuery Agentic AI Staff Software Engineer at Google BigQuery focused on building agentic AI solutions for data processing. The role involves designing and developing systems that integrate LLMs with BigQuery, architecting agents for reasoning over large datasets, optimizing pipelines, and contributing to agentic frameworks with tool use and evaluation. This position is at the intersection of distributed systems and generative AI. | Agent | 9 |
| Senior Software Machine Learning Engineer, DeepMind Senior Software Machine Learning Engineer at Google DeepMind focused on building and testing advanced AI agents. Responsibilities include creating agentic workflows, engineering runtime infrastructure for LLMs, partnering with researchers, and designing evaluation frameworks. The role involves working with Gemini models, testing on robots, and ensuring production reliability. | Agent |
| 9 |
| AI Research Scientist, Applied AI, Google Cloud Research Scientist role focused on designing, developing, and deploying agentic AI solutions for enterprise use cases within Google Cloud's Applied AI division. The role involves taking ownership of AI quality, implementing and advancing AI techniques, and driving progress through experimentation. It requires a PhD, experience leading research, and applied ML experience, with a focus on enterprise AI solutions and collaboration with model builders. | AgentPost-train | 9 |
| Staff AI Research Scientist, Applied AI, Google Cloud Staff AI Research Scientist role focused on designing, developing, and deploying scalable and agentic AI solutions for enterprise use cases within Google Cloud's Applied AI team. The role involves taking ownership of AI quality for production systems, implementing evaluation frameworks, and advancing AI techniques through experimentation. It requires a PhD, experience with ML algorithms and LLMs, and a publication record, with a focus on applied research and product contribution. | AgentEval Gate | 9 |
| Software Engineer, Applied AI Software Engineer, Applied AI at Google, focusing on deploying and maintaining production-grade AI agents for Gemini Enterprise. Responsibilities include prompt engineering, fine-tuning, CI/CD, and monitoring agent performance. Requires experience with generative AI agents, ML infrastructure, and potentially speech/audio or reinforcement learning. | AgentPost-train | 9 |
| Research Engineer, Frontier Safety Mitigations, DeepMind Research Engineer focused on developing and deploying advanced safety mitigations for frontier AI models, specifically defending against misuse in domains like Cybersecurity and CBRNE. The role involves building classifiers, data pipelines, monitoring systems, and evaluating agentic AI systems, with a strong emphasis on automated red-teaming and adversarial robustness. | AgentEval Gate | 9 |
| Research Software Engineer, Multimodal AI This role focuses on developing and enhancing AI agents, particularly in the multimodal domain (audio, vision), for XR devices. The engineer will work on LLMs, agents, and their integration into next-generation computing products, involving algorithm development, production-quality coding, evaluation planning, and shipping AI innovations. The role requires experience in software development, generative AI, ML frameworks, and multimodal learning. | AgentPost-train | 9 |
| Staff Software Developer, AI/ML, Safety and Security This role involves leading AI/ML projects focused on safety and security within Google Workspace. The primary responsibilities include building LLM-based safety and security auto-raters, developing classifiers for prompt injection attacks, and implementing live traffic observability solutions. The role also requires collaboration with Google DeepMind on research-based defense techniques and with various Workspace product teams to protect AI features. The ultimate goal is to ensure the safety and security of AI features across Google's productivity tools. | AgentServe | 9 |
| Forward Deployed Engineer V, Generative AI, Google Cloud This role involves deploying and building bespoke agentic AI solutions for enterprise customers on Google Cloud. The engineer will bridge the gap between frontier AI products and production reality, addressing integration, data readiness, and state-management challenges. Responsibilities include developing complex AI applications, architecting connective tissue between AI products and customer infrastructure, building evaluation pipelines and observability frameworks, identifying field patterns for product feedback, and co-building with pre-sales and product teams. The role requires strong software development experience, experience with production-grade AI solutions, and building data pipelines using vector databases and RAG. Experience with multi-agent systems and LLM-native metrics is preferred. | AgentServe | 9 |
| Staff Software Engineer, Quality, Google Cloud, Applied AI Staff Software Engineer focused on building and improving AI agents, specifically a meta-layer of agents that build, test, and refine other agents. The role involves developing multi-modal customer support agents with complex reasoning capabilities, embedding Gemini and Vertex AI into client-facing infrastructure, and establishing engineering benchmarks for automated optimization and AI quality assurance in production systems. | AgentEval Gate | 9 |
| Staff Software Engineer, AI Infrastructure, Google Cloud, Applied AI Staff Software Engineer focused on building and scaling high-performance, distributed infrastructure for agentic AI workflows in Google Cloud. The role involves transitioning experimental models into robust production services, ensuring low-latency and reliability for multi-agent systems, and iterating on customer needs for enterprise use cases. | AgentServe | 9 |
| Senior Software Engineer, Google Cloud, Applied AI Senior Software Engineer at Google Cloud focused on developing and deploying agentic AI solutions for enterprise use cases, leveraging Gemini Enterprise. The role involves algorithmic innovations for multi-agent systems, reinforcement learning, multimodal reasoning, and improving LLM reliability and tool use. | Agent | 9 |
| Research Scientist, Robotics, DeepMind Research Scientist at Google DeepMind Robotics focused on building foundation models like vision-language-action (VLA) models for physical agents, enabling robots to perceive, plan, think, use tools, and act. The role involves research into agentic reasoning, real-world understanding, and robot control, with a focus on publishing research and contributing to the AI research community. | AgentPost-train | 9 |
| Research Engineer, Embodied Agents, DeepMind Research Engineer at DeepMind focused on building AI agents that operate in physical environments, advancing physical AGI. The role involves designing learning infrastructure, collaborating with partners for deployment, and building developer tools for robotics capabilities. Key challenges include bridging the gap between simulation and real-world robot performance. | AgentServe | 9 |
| Senior Staff Technical Program Manager, AI Innovation and Research The Technical Program Manager will drive the strategy and execution of AI agent initiatives aimed at transforming the software development lifecycle, including democratizing app creation and building a virtual software engineering workforce. This role involves leading complex, cross-functional programs from 0-to-1, bridging foundational models with product applications, and ensuring safety and compliance. | Agent | 9 |
| Senior Software Engineer Senior Software Engineer at Google DeepMind focused on building and improving agentic AI features using Gemini models. The role involves developing quantitative evaluations of agent performance, triaging production issues, and contributing to the technical vision and roadmap. Requires a PhD in a related field and experience in software development, algorithm design, systems architecture, Python for ML, and software testing. | AgentEval Gate | 9 |
| Research Scientist, Manipulation for Robotics, DeepMind Research Scientist role focused on pioneering AI integration into robotics for physical agents, enabling robots to perceive, plan, think, use tools, and act. The role involves developing and training large foundation models for general-purpose dexterous manipulation tasks, aiming for human-level performance on real-world applications using frontier robotics models. This includes working with simulators, real robots, and various AI techniques like reinforcement learning and vision-language-action models. | AgentData | 9 |
| Software Engineer III, Multimodal Agentic AI, XR This role focuses on designing, developing, and deploying multimodal agentic AI solutions for smart glasses, leveraging Gemini Live and Astra. It involves enhancing multimodal tools, defining strategies for data, evaluation, and post-tuning of Gemini models, and optimizing agent architecture for inference cost. The role emphasizes AI quality for production systems, including evaluation frameworks and model improvements, with a focus on multimodal conversational quality, tool use, and goal-oriented reasoning. | AgentPost-train | 9 |
| Forward Deployed Engineer III, Generative AI, Google Cloud This role involves deploying and building bespoke agentic AI solutions for enterprise customers on Google Cloud. The engineer will integrate Google's AI products with customer infrastructure, address integration complexities, data readiness, and state management issues. They will also build evaluation pipelines and observability frameworks, and act as a feedback loop to product teams. The role requires strong software development skills, experience with cloud platforms, and building production-grade AI solutions, including RAG and multi-agent systems. | AgentEval Gate | 9 |
| Staff Software Engineer, Generative AI, Search Developer Tools Staff Software Engineer focused on Generative AI for Search Developer Tools, specifically leveraging agentic development to improve product velocity for AI Overviews and AI Mode. The role involves leading the architecture, design, and development of scalable agentic solutions, improving human-AI collaboration, and integrating tools and skills within the Google ecosystem. | Agent | 9 |
| Staff Software Engineer, Machine Learning, Google Chat Staff Software Engineer, Machine Learning for Google Chat, focusing on building and scaling AI infrastructure for enterprise collaboration. The role involves architecting agents, developing GenAI capabilities like RAG and personalized assistants, and optimizing inference costs. Key responsibilities include leading AI-scaled evaluation loops, owning the RAG roadmap, automating NLU bug resolution, and optimizing the AI stack for performance and cost efficiency, with a strong emphasis on bridging AI research and production systems. | AgentServe | 9 |
| AI Application Engineer This role focuses on building AI agents and advanced analytics pipelines to optimize data center hardware and processes, turning complex datasets into actionable insights. The engineer will lead foundational development for these agents, including data pipelines and API creation, and apply AI/ML techniques to solve operational challenges and predict anomalies. The role also involves partnering with stakeholders to drive automation and innovation. | AgentData | 8 |
| Senior Business Data Scientist, AI/ML, Google Cloud Senior Business Data Scientist focused on AI/ML for Google Cloud customer support. The role involves developing and deploying predictive, personalized, and proactive solutions using LLMs and intelligent autonomous agents. Key responsibilities include end-to-end development, implementing evaluation frameworks for LLMs and agents, monitoring production systems, and identifying AI/ML opportunities through stakeholder collaboration. The role emphasizes translating business needs into technical requirements and integrating advancements in generative AI and agent architectures. | AgentEval Gate | 8 |
| Field Solutions Architect III, Generative AI, Google Public Sector Field Solutions Architect for Google Public Sector, focusing on building rapid prototype generative AI applications for public sector customers. This role involves leveraging generative AI technologies, collaborating with product teams, and disseminating lessons learned. Responsibilities include designing end-to-end genAI solutions, demonstrating Google Cloud capabilities, building repeatable technical assets, and influencing product direction. Requires experience in applied AI with foundation models, prompt engineering, fine-tuning, RAG, and orchestrating model interactions, along with cloud platform experience and a security clearance. | AgentPost-train | 8 |
| Lead GenAI Forward Deployed Engineer, YouTube Google is seeking a Lead GenAI Forward Deployed Engineer for their YouTube AI Accelerator team. This role focuses on driving AI transformation for YouTube's business operations by redesigning workflows and deploying applied AI solutions. The engineer will build GenAI PoCs, lead the delivery of complex AI applications from prototype to production, and act as a trusted engineering partner. Responsibilities include authoring technical designs, writing code, building front-ends, and developing high-performance eval pipelines and observability frameworks to address AI bottlenecks. | AgentEval Gate | 8 |
| Senior Software Engineering Manager, Agentic Platform, Cloud Security Manage a team of engineers building a Security Agentic Platform for Google Cloud Security Operations, enabling security agents and protecting organizations worldwide. The role involves technical leadership, team management, and overseeing the end-to-end development lifecycle of AI-driven agentic security solutions. | Agent | 8 |
| Senior Staff Model UX Designer, GeminiApp, DeepMind Senior Staff Model UX Designer for Gemini App at DeepMind, focusing on shaping conversational AI experiences from passive responders to proactive partners. The role involves collaborating with PMs, engineers, and researchers to build end-to-end product experiences, guide prompt engineering, initiate qualitative assessments of model performance, and craft multimodal solutions. Requires deep understanding of model capabilities and the eval process, with a focus on user engagement and product innovation in generative AI. | Agent | 8 |
| Surfaces Model UX Designer, GeminiApp, DeepMind This role focuses on designing the user experience for Gemini's mobile assistant, specifically for multimodal and voice interactions. The designer will work with advanced AI models to refine responses, optimize context switching, and ensure intuitive and reliable user interactions. Responsibilities include defining conversational structures, implementing system instructions, and conducting qualitative assessments of model performance. The role requires experience in conversational AI/LLMs and designing for multimodal and voice entry points. | Agent | 8 |
| Director, Product Management, SecOps Detections, Google Cloud Security The Director of Product Management will lead the product vision for Google SecOps detection capabilities, focusing on AI/ML integration to create an autonomous SOC. This role involves collaborating with AI researchers and security engineers to develop dynamic detection models, design automated workflows using Generative AI, and integrate advanced ML capabilities into massive telemetry streams for enterprise customers. | AgentPost-train | 8 |
| Director, Product Management, SecOps Responses, Google Cloud Security Product Management Director for an AI-powered security platform, focusing on autonomous threat remediation and Generative AI-driven response strategies within Google Cloud Security. The role involves leading product vision, harnessing LLMs for incident synthesis and remediation plan generation, and building intelligent orchestration workflows for proactive threat containment. | Agent | 8 |
| Staff Software Engineer, Search Agentic Ecosystem Platform Staff Software Engineer to build the foundational platform for Google Search's Agentic Ecosystem, enabling AI Mode and Gemini to interact with third-party services for task completion. The role involves architecting core infrastructure, building use cases, ensuring cross-platform compatibility, and providing technical leadership. | Agent | 8 |
| Staff Software Engineer, Gemini Enterprise Staff Software Engineer role at Google focused on building the backend infrastructure and services for Gemini Enterprise, an AI platform for enterprise data. The role involves architecting orchestration layers for LLMs and agentic workflows, integrating Generative AI tools, and partnering with cross-functional teams to deliver solutions for Cloud customers. Experience with C++, Java, Python, Go, software design, architecture, and integrating Generative AI tools is required. | AgentServe | 8 |
| Senior Staff Software Engineer, Gemini Enterprise Senior Staff Software Engineer role focused on building the core backend infrastructure and services for Gemini Enterprise, an AI platform for generative search, assistant, and agent applications over enterprise data. The role involves architecting orchestration layers and frameworks for LLMs and agentic workflows, integrating Generative AI tools, and partnering with cross-functional teams to deliver high-impact solutions for Cloud customers. | AgentServe | 8 |
| Staff Software Engineer, Cloud AI Staff Software Engineer for Google Cloud's Gemini Enterprise, focusing on backend infrastructure, orchestration layers for LLMs and agentic workflows, and platform features. The role involves integrating Generative AI tools and LLM interfaces into enterprise solutions, partnering with cross-functional teams to leverage Google's AI models and GCP technologies for Cloud customers. | AgentServe | 8 |
| Software Engineer, ML Fleet Intelligence Software Engineer, ML Fleet Intelligence at Google, focused on applying AI/ML to predict, detect, and mitigate hardware and software faults across a global fleet of data centers and ML TPUs. This role involves leveraging large-scale data, optimizing ML infrastructure, and building automated systems to ensure reliability and uptime. | AgentServe | 8 |
| Forward Deployed Engineer, DeepMind This role embeds with strategic partners to architect, optimize, and build production-grade GenAI applications, driving joint evaluations and benchmarking to influence model development. It involves guiding partners on advanced implementation techniques like RAG and multimodal integrations, and building feedback loop tooling. | AgentEval Gate | 8 |
| Senior Software Engineering Manager, Agent Registry and AppHub Senior Software Engineering Manager at Google Cloud responsible for the Agent Registry and AppHub. This role focuses on building foundational infrastructure for an AI-native agentic cloud, managing teams, and driving best practices for distributed systems and AI/LLM adoption. Key responsibilities include owning multi-year roadmaps, transforming AppHub into a central registry for AI Agents, and delivering infrastructure for agentic observability and regulatory reporting. | Agent | 8 |
| Software Engineering Manager II, Agentic Planning and Memory Software Engineering Manager II for the Agentic Planning and Memory team, focused on building next-generation agentic capabilities for Google Workspace. The role involves developing advanced general function-calling approaches for autonomous workflow execution and an agentic memory layer for improved context retention, accuracy, personalization, and latency. The manager will lead teams, define technical roadmaps, and collaborate on integrating these capabilities into core Workspace products, impacting billions of users. | Agent | 8 |
| Senior Software Engineer, AI/ML, Geo and Gemini App Senior Software Engineer role focused on building AI/ML features for Google Geo products, involving agentic workflows, evaluation frameworks, and serving infrastructure enhancement. Requires experience with LLMs, RAG, and model quality optimization. | AgentEval Gate | 8 |
| Principal Consultant, AI/ML, Mandiant, Google Cloud This role focuses on architecting and building intelligent agents and tooling to automate cyber defense operations. The consultant will translate complex security workflows into AI systems, integrate them with enterprise platforms, and ensure their operational readiness and security. The role requires experience with AI platforms, Generative AI agents, Python, and integrating distributed systems, with a preference for cybersecurity operations and AI evaluation frameworks. | Agent | 8 |
| Staff Software Engineer, Knowledge Catalog, AI Staff Software Engineer role focused on empowering AI agents within Google Cloud's data ecosystems. The role involves tackling challenges in context engineering, metadata enrichment, search, personalization, conversational analytics, and catalog infrastructure, with a focus on rapid prototyping, experimentation, and integration with products like Gemini Enterprise. The engineer will drive technical goals, influence across boundaries, shape strategy, and lead junior engineers, with a minimum of 8 years of software development experience and 5 years of experience in ML infrastructure and GenAI techniques. | AgentServe | 8 |
| Staff Software Engineer, Roads Data Quality, Geo Staff Software Engineer role focused on designing and building a 3D navigation map using sensor data, large ML models, and vision transformers. The role involves leading ML model development, data curation, evaluation, and deploying GenAI solutions. It requires technical leadership and collaboration across multiple teams. | AgentData | 8 |
| Senior Software Engineering Manager, Ecosystems and Integrations Databases Senior Software Engineering Manager to lead a team focused on transforming Cloud databases for agentic AI. The role involves managing engineers, contributing to product strategy, and overseeing the deployment of large-scale projects. The team's mission is to build common platforms and frameworks to support agents on all databases, enabling them to use enterprise data effectively. This requires balancing research in AI and databases with shipping products. | Agent | 8 |
| Staff Software Engineer, AI/ML, XR Staff Software Engineer focused on building AI-powered interactions for next-generation XR devices, integrating Gemini's multimodal capabilities to create personalized and contextually aware experiences. The role involves innovating and architecting multimodal solutions, collaborating cross-functionally, and developing technologies for intelligent eyewear and VR headsets. | Agent | 8 |
| Staff Datacloud Blackbelt Engineer, Data and AI Staff Blackbelt Engineer focused on building, deploying, and optimizing sophisticated Data and AI agents and solutions for enterprise customers using Google's AI technologies. The role involves architecting solutions, optimizing performance, and codifying reusable assets for broader adoption, bridging platform primitives with customer needs. | AgentServe | 8 |
| Senior Software Engineer, Map Ads, Machine Learning Senior Software Engineer role focused on building next-generation modeling and quality infrastructure for queryless ad formats using advanced AI techniques like LLM-based distillation and differential modeling. The role involves leading technical roadmaps across retrieval, auction, and measurement, and developing evaluation frameworks. It requires experience with ML infrastructure, programming, and machine learning fields such as reinforcement learning, recommendations/ranking, or LLMs. | AgentPost-train | 8 |
| Staff Software Engineer Staff Software Engineer at Google DeepMind focused on building tools and best practices for AI research iteration, architecting data pipelines for training and evaluation, and developing evaluation benchmarks. The role involves collaborating with researchers to ship product features and providing technical leadership, with a strong emphasis on system design, scalability, and maintainability. | AgentEval Gate | 8 |
| Software Engineer Software Engineer role at Google DeepMind focused on applying research to high-impact problems by prototyping GenAI solutions, curating datasets, and building ML pipelines for generative media, multimodal understanding, and reinforcement learning. The role involves developing robust product code, designing and building infrastructure for next-gen AI features, and managing the full deployment lifecycle. | AgentData | 8 |
| Staff Software Engineer, Agentic AI, Trust and Safety Staff Software Engineer role focused on architecting and scaling AI/ML systems and distributed infrastructure for Trust and Safety at Google. The role involves defining the technology roadmap, integrating high-availability systems, leading multi-team technical initiatives, and mentoring other engineers. Requires experience in large-scale distributed systems and building agentic AI systems. | AgentServe | 8 |
| Senior Staff Tech Lead, YouTube Shorts Discovery Tech lead for AI/ML software engineers focused on YouTube Shorts discovery models, aiming to align recommendations with user interests. This involves building large-scale AI/ML systems using techniques like LLMs, generative retrieval, and long-sequence modeling for personalized retrieval and early-stage ranking. The role requires defining technical strategy, leading high-impact projects, and partnering with cross-functional teams. | AgentServe | 8 |
