Google

Solutions Architect for Google Cloud, focusing on the Data Cloud portfolio (Databases, Big Query, Looker) and Vertex AI. The role involves working with customers and internal teams to design and present technical solutions, create technical collateral, and provide customer feedback to Product and Engineering. Requires experience with data pipelines, warehousing, SQL/NoSQL, Python/Java, and Google Cloud's Vertex Platform, with preferred experience in architecting unified Data and AI/ML platforms for Generative AI.

Google is seeking a Staff Software Engineer to work on Woodshed, an AI/ML Storage system that provides exabyte-scale foundation for all ML workloads at Google, aiming to accelerate ML training and inferences and simplify ML data management. The role involves technical leadership, project management, and collaboration with infrastructure and client teams to guide integrations for high-impact projects.

This role focuses on building and maintaining a high-performance telemetry infrastructure to support demanding workloads, including LLM training. The engineer will write product/system development code, participate in design reviews, review code, contribute to documentation, and triage/debug system issues. While the role supports AI workloads, its core craft is infrastructure and telemetry, not direct AI/ML model development.

This role focuses on guiding Public Sector customers in developing, configuring, and deploying their data and AI solutions on Google Cloud Platform. It involves providing architecture guidance, supporting ML model development and deployment, and ensuring optimal data pipeline performance. The role requires strong data engineering skills, experience with relational databases and object-oriented programming, and the ability to translate business requirements into technical solutions.

Engineering Manager for Google's Sole Tenancy AI and Compute team, focusing on enterprise cloud adoption and intelligent host management. The role involves leading a team to deliver AI and Infrastructure at scale, supporting Google's AI models and cloud platform.

Customer Engineer for Google Public Sector focusing on national security, partnering with technical sales teams to understand customer needs, develop cloud solutions, and troubleshoot technical issues. This role involves working with Assured Workloads, Google Distributed Cloud, and Cloud AI to ensure secure data processing and analysis for sensitive government data. Responsibilities include building go-to-market solutions, owning technical relationships with partners, providing integration strategy recommendations, and performing work with specialized equipment in Google Distributed Cloud environments. Requires experience with air-gapped deployments, classified systems, and generative AI capabilities, along with a Top Secret/SCI security clearance.

Senior Staff Software Engineer, Front End, Google Workspace. This role focuses on the technical direction and architecture of web and mobile applications for Google Workspace products like Gmail, Docs, and Drive. The engineer will define and drive technical goals for new features, lead design and architecture, provide technical leadership and mentorship, and collaborate with cross-functional teams. While the role is not directly building AI models, it is at the forefront of integrating AI into productivity tools and will work closely with AI model builders.

Staff Software Engineer for Cloud SQL, MySQL, focusing on integrating agentic AI to enhance customer backend management. Responsibilities include architectural design, roadmap contribution, and technical leadership within the MySQL community and Google Cloud Platform.

This role is for a Software Engineering Manager at Google, leading a team that builds internal and external tooling for sales, marketing, and service teams within the Global Business Organization (GBO). The team will architect and develop web applications and services on Google infrastructure, integrating core technologies including Gemini for agentic features. The role involves technical leadership, people management, defining technical goals, and driving strategic execution of a new platform. While AI (Gemini) is mentioned as an integration point, the core focus is on building tooling and applications, not on developing AI models or core AI infrastructure.

Software Engineer role focused on Cloud Infrastructure Engineering, specifically on delivering efficient compute solutions for Google Cloud. The role involves optimizing resource usage, collaborating with data science teams on statistical modeling for capacity planning, integrating resource management tools, and developing new cluster management products. The work impacts both ML and non-ML use cases, aiming to improve compute and ML resource efficiency for financial and environmental benefits.

This role is for a Senior Software Engineer on the Google Workspace team, focusing on infrastructure. While the team works with AI models built by Google DeepMind and aims to integrate AI into productivity tools like Gmail and Docs, the core responsibility of this role is software engineering for infrastructure, not direct AI/ML model development or research. The role involves designing, developing, testing, and maintaining software solutions that support these AI-enhanced products.

Customer Engineer role focused on AI infrastructure and accelerators within Google Cloud, helping enterprise clients integrate and optimize AI/ML models. Responsibilities include advising on cloud strategy, demonstrating product differentiation, building reusable assets, and influencing product roadmaps. Requires strong cloud infrastructure experience and experience building/operationalizing ML models, with preferred experience in training large models and performance profiling.

This role focuses on using and improving Large Language Models (LLMs) for content moderation and anti-abuse efforts on YouTube. Responsibilities include designing and refining prompts for LLMs, analyzing data to understand abuse impact, and driving experiments to prevent abuse. The role involves working with data, identifying product vulnerabilities, and collaborating with engineers and stakeholders.

Customer Engineer III for Google Cloud's Healthcare and Life Sciences (HCLS) sector. This role partners with technical sales teams to serve as the customer's primary technical advisor, understanding business issues, troubleshooting, conducting proofs of concept, and architecting cross-pillar cloud solutions. The focus is on driving technical wins and defining delivery/consumption plans, blending sales expertise with technical engagement to prove the value of Google Cloud.

This role focuses on ensuring the quality and reliability of Google's GPU-based AI hardware infrastructure within their Cloud offerings. The Product Quality Engineer will lead quality initiatives, collaborate with manufacturing partners, develop predictive failure models, and drive issue resolution throughout the product lifecycle, from concept to End-of-Life. While the role supports AI infrastructure, the core craft is hardware quality engineering, not direct AI/ML model development.

This role is for a Software Engineer III on the Google Workspace Infrastructure team, focusing on building AI-powered productivity tools for the future of work. The engineer will write product or system development code, participate in design reviews, review code, contribute to documentation, and triage/debug system issues. The role involves working with AI model builders and impacting billions of users by enhancing products like Gmail, Docs, and Meet with AI capabilities such as pre-computed summaries and AI avatar-generated videos.

Customer Engineer III for Google Public Sector, focusing on technical sales and architecting Google Cloud solutions for state and local government and education clients. Responsibilities include developing technical account plans, demonstrating Google Cloud value through demos and pilots, architecting cross-pillar solutions, and facilitating post-sales transitions. Requires experience with cloud-native architecture, customer-facing roles, and cloud infrastructure engineering. Preferred qualifications include experience with public sector clients, migrations, security, networking, and generative AI tools.

Manage a team of Software Engineers to build and scale video infrastructure for Google Meet, focusing on AI-driven productivity features. This role involves technical leadership, people management, and contributing to product strategy for AI-enhanced tools.

Manage a team of engineers developing debug and analytics tools for Google's custom silicon (e.g., tensor), utilizing GenAI to pinpoint silicon issues and enhance productivity. The role involves HW/SW co-design and leading the DTA Tools team in Taipei.

Software Engineer focused on AI security within Google Cloud, responsible for designing and developing security services for AI, collaborating on productization, ensuring service availability, and mentoring team members. Requires 5 years of software development experience and 3 years of experience with software products, design, and architecture.

Software Engineering Manager for Google's Global Networking Technology team, focusing on leading teams, managing large-scale projects, and contributing to product strategy. The role involves optimizing code, managing engineers, and overseeing the deployment of large-scale projects. The AI and Infrastructure team aims to deliver AI and Infrastructure at scale, supporting Google's AI models and global services.

This role is for a Research Data Scientist on the YouTube Gaming Discovery team, focusing on helping gamers find content and playable mini-games within the YouTube app. The role involves collaborating with stakeholders, designing and evaluating models, and using data infrastructure to solve product or business problems. It requires experience with analytics, coding, and querying databases, with a preference for machine learning and recommender systems.

Software Engineer III at Google Beam, focusing on real-time ML-based 3D human capture and rendering for live 3D experiences. The role involves developing scalable software regression frameworks, automated release test infrastructure, and Hardware-in-the-Loop (HILT) testing for Google Beam's communication technology.

This role focuses on developing and implementing strategies to enforce YouTube policies at scale, leveraging Machine Learning and Large Language Models (LLMs) for abuse prevention and detection. The analyst will collaborate with engineering, product, and policy teams, provide incident response, and design prompts for LLMs to improve content identification and classification.

Google is seeking an Engineering Manager for their Switch Stack Software team. This role involves technical leadership, people management, and contributing to the development and maintenance of high-quality, high-availability, high-performance switch operation systems deployed in Google data centers. The team's work directly supports the growth of AI initiatives like Gemini and Google Cloud business, and involves shaping the future of global networks by engaging with both hardware and software aspects of networking infrastructure.

Software Engineer III, Full Stack, Shopping on Gemini at Google in Zurich, Switzerland. This role focuses on building innovative consumer experiences for Shopping within Gemini, leveraging GenAI advancements. Responsibilities include full-stack development, code reviews, debugging, and contributing to documentation. Requires a Bachelor's degree, 2 years of software development experience, 2 years of full-stack experience, and 1 year of data analysis experience. Preferred qualifications include experience building LLM-based applications and managing feature development.

This role focuses on enabling agentic development within the Search Ads domain by identifying and resolving infrastructure hurdles, creating new agentic workflows, and providing guidance and support to development teams. The role involves leading a virtual team and collaborating with various infrastructure and DevAI groups.

This role focuses on managing and mitigating payment fraud and abuse for Google products, investigating incidents, performing statistical analysis, and collaborating with engineering teams to enhance tools and systems. It involves assessing product risk, designing mitigation strategies, and working with cross-functional teams to launch solutions. While it uses ML systems and has preferred qualifications in ML/LLMs, the core function is risk management and fraud prevention, not direct AI model development.

This role is for a Senior Staff Software Engineer on the Google Cloud Run Serverless platform team. The primary focus is on providing technical leadership and overseeing the architectural strategy for core back-end services, with an emphasis on the data plane to support evolving AI workloads and agents. The role involves influencing and coaching engineers, driving operational excellence, and collaborating with leadership on long-term goals for stack modernization and platform sustainability. While the role supports AI workloads, it is not directly building AI models or agents, but rather the underlying infrastructure.

Staff Software Engineer role at Google focused on Ads Campaign Automation, leveraging Generative AI for asset generation and optimizing ad serving, bidding, and retrieval systems. Requires strong experience in ads buying platforms, large-scale distributed systems, and the Google ads ecosystem, with fluency in Mandarin for regional collaboration.

Staff Software Engineer, Full Stack for Google One, a subscription service that combines cloud storage with AI features. The role involves technical leadership, roadmap definition, architecture, and contributing to AI business generation goals by prototyping and launching new subscription experiences.

This role is for a Silicon Validation Lead focused on AI/ML hardware acceleration, specifically Tensor Processing Units (TPUs). The lead will manage a team responsible for the post-silicon validation of AI/ML SoCs, ensuring timely bring-up, enablement, and debug. The role involves close collaboration with various engineering teams (architecture, design, verification, firmware, software, platform) and people management responsibilities.

This is a PhD intern role focused on developing and maintaining the end-to-end infrastructure for AI-integrated software and large-scale systems at Google. The intern will work on complex computer science solutions and scalable, distributed software systems.

Customer Engineer III for Google Cloud in the federal public sector, focusing on technical sales support, solution architecture, and customer engagement. The role involves understanding customer needs, demonstrating Google Cloud capabilities, and addressing technical challenges, with a specific requirement for experience in designing and deploying solutions that integrate generative AI and knowledge of cloud compliance requirements like FedRAMP and CMMC.

Staff Software Engineer at Google Cloud focused on optimizing fleet transformation and operations using ML-powered simulations and discrete algorithms. The role involves migrating from MIP models to ML for predictive, self-governing systems, designing simulation engines, and guiding automated policy enforcement for AI/ML compute needs.

This role is for a PhD Software Engineer focused on Fleet Analytics within Google Cloud's AI and Infrastructure organization. The role involves designing, developing, and maintaining software solutions, with a focus on advanced optimization models. While the organization works with AI/ML systems, this specific role's primary output is optimization models and platform capabilities, not direct AI/ML model development or deployment.

Manage a team developing next-generation AI/ML networking solutions and Smart NICs, focusing on the hardware-software interface for AI training and inference transport layers, and dataplane encryption. The role involves leading software development in C++ for these solutions, aligning strategy, and ensuring projects move from development to production.

This role focuses on the verification of AI/ML hardware accelerators (TPUs) for Google Cloud. The engineer will be responsible for the full verification life-cycle, ensuring the reliability and performance of AI/ML workloads on TPU hardware. This involves creating verification environments, identifying coverage measures, debugging, and collaborating with design engineers. While the role is deeply involved with AI/ML hardware, the core craft is hardware verification engineering, not AI/ML model development or research.

Engineering Manager for Google Home Growth, focusing on hardware, software, and AI to grow the subscription business. Responsibilities include setting team priorities, managing engineers, developing technical roadmaps, guiding system designs, and reviewing code. Requires experience in software development, Android development, and technical/people management.

Software Engineering Manager for Google Global Infrastructure, NetSoft team. This role involves managing engineers, providing technical leadership, and contributing to product strategy. The team's mission is to enable agile planning, optimized design, and rapid deployment for Google's networks. The role will work on software systems for network planning, modeling, simulations, and risk assessment, with a focus on enabling AI/ML and Cloud expansions at scale.

Senior Software Engineering Manager for Google Cloud Dataproc, responsible for building an AI-ready platform with GPU support and integrating AI/ML/Data Science workloads. The role involves leading engineering teams, architecting data lakehouse solutions, and fostering innovation in distributed systems and open-source technologies.

This role focuses on enterprise security for AI products, specifically assessing and securing AI agents and features. The engineer will develop threat models, implement guardrails, and advise on mitigating risks associated with AI use within Google's products and third-party AI products.

This role is for an Engineering Manager to lead teams focused on sharing infrastructure and UI primitives that integrate AI experiences, particularly for products like Gemini. The manager will own strategy, technical roadmaps, and people management, ensuring architectural decisions align with organizational priorities and leveraging AI/ML tools to enhance team velocity. The focus is on shipping AI-powered user experiences and driving adoption through sharing features.

Senior Staff Software Engineer role focused on Google's Local Ads product, aiming to improve user experience and advertiser ROI. Responsibilities include identifying business opportunities, leading product design and development, and designing experiments. Requires experience in software development, system design, and online advertising platforms, with a focus on data analytics, statistical modeling, and machine learning.

Google is seeking a Software Engineering Manager for their Switch Infrastructure team in Bengaluru, India. This role involves leading and mentoring a team of engineers responsible for the testing and validation of Google's network switch hardware and software. The team's work is critical for supporting all major Google services, including AI/ML infrastructure like Gemini, and focuses on advancing network infrastructure for scalability, agility, reliability, and innovation. The manager will define strategy, drive execution, collaborate with cross-functional teams, and foster a culture of engineering excellence. Minimum qualifications include a Bachelor's degree, 8 years of software engineering/test automation/network engineering experience, experience with Ethernet switches, C++/Python development, team leadership, and data center networking.

Tech Lead for YouTube's core server infrastructure, responsible for technical strategy, leading an engineering team in architecting high-performance solutions, and innovating with machine learning for personalized viewer experiences.

Software Engineer role focused on developing debugging, profiling, and analytics tools for Google Cloud. The role involves working with large-scale systems and exploring the use of machine learning for anomaly detection in cloud control plane systems.

Technical Solutions Engineer for Google Cloud's Data Analytics and AI/ML services, focusing on troubleshooting and resolving customer-reported issues. Requires strong technical skills in data, AI/ML, and coding, with fluency in Japanese and English.