Global Alliance Lead, GSI and Consulting Partnerships, Google Cloud

🏢 Summary: Customer Engineer role partnering with sales teams to design and demonstrate Google Cloud solutions for customers. The position leads technical discovery, demos, pilots, solution architecture, and delivery planning to win and expand cloud workloads. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 6 years of cloud computing experience, 6 years of presentation delivery experience, Experience presenting to technical stakeholders and executive leaders 📃 Skills: Cloud, GoogleCloud, A2A, LangGraph, CrewAI, AutoGen, VertexAI, LLM, TTFT, MCP, Authentication, Quantization 🏢 Description: Minimum qualifications • Bachelor's degree or equivalent practical experience. • 6 years of experience with cloud computing and delivering presentations. • Experience engaging with, and presenting to, technical stakeholders and executive leaders. Preferred qualifications • Experience navigating AI infrastructure consumption models and optimizing high-throughput training/inference clusters. • Experience implementing multi-agent systems using frameworks such as A2A, LangGraph, CrewAI, and AutoGen. • Experience navigating the startup life cycle, from initial prototyping with AI Studio to scaling and achieving product-market fit on Vertex AI. • Experience working with, and a passion for, the high-growth startup ecosystem and its typical rapid-scaling issues. • Knowledge of LLM-native performance metrics, including TTFT, tokens/sec, and cost-per-request, and techniques for optimizing state management, quantization, and provisioned throughput. • Ability to implement secure agentic workflows incorporating MCP, tool-calling, and enterprise-grade authentication. About the job As a Customer Engineer, you will partner with technical sales teams to differentiate cloud solutions for customers. You will serve as the customer’s primary technical partner and trusted advisor, leading technical conversations to understand business issues. You will troubleshoot technical questions and roadblocks, participate in proofs of concept and demos, and architect cross-pillar cloud solutions. You will drive the technical win, define delivery and consumption plans, and present practical solutions to technical and business leaders. You will identify, pursue, and win new business workloads while expanding existing ones. The role requires broad technical expertise across infrastructure modernization, application modernization, data analytics, and related areas, combined with sales expertise, market knowledge, and direct technical engagement. Responsibilities • Develop and own the technical account plan and strategy, participating in planning and supporting targeted sales motions. • Combine sales, programming, and solutions architecture expertise to prove the value of the cloud portfolio through complex demos, pilots, and in-depth workshops. • Architect cross-pillar solutions, drive technical wins, and define initial delivery plans for customers; continue to lead technical engagement during the solution phase. • Facilitate the post-sales transition by supporting pricing activities and transitioning the final delivery plan to implementation teams. • Maintain awareness of progress against the delivery plan, providing support to cross-functional teams during ramp, delivery, migration, or implementation phases.

🏢 Summary: This offer is for a senior software engineer to build conversational AI-agent capabilities, including recommendation systems, skill discovery and performance investigation tools. The role combines ML system design and infrastructure with technical leadership, stakeholder management and team coaching. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 5 years of software development experience, 5 years of software product testing and launch experience, 3 years of software design and architecture experience, 5 years of experience in speech/audio, reinforcement learning, ML infrastructure, or another ML specialization, 5 years of ML design and ML infrastructure experience, including deployment, evaluation, data processing, debugging or fine-tuning 📃 Skills: Python, MachineLearning, ReinforcementLearning, Speech, Audio, MLOps, Deployment, Evaluation, Debugging, Finetuning, Algorithms, Architecture 🏢 Description:

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🏢 Summary: Security Advisor role leading enterprise security transformations across North America and Latin America. The position focuses on maturing Security Operations through SIEM/SOAR, multi-cloud threat visibility, detection engineering, and AI-driven automation while advising executive stakeholders. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 7 years of experience architecting, developing, or maintaining secure cloud solutions, Experience with system design or reading code, Experience with SecOps offerings and the cybersecurity vendor landscape, Fluent English and Spanish communication skills 📃 Skills: SIEM, SOAR, SecOps, Java, C++, Python, Cloud, GCP, AI, CSPM, SaaS, GTI, CEP 🏢 Description: Qualifications Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 7 years of experience architecting, developing, or maintaining secure cloud solutions. • Experience in either system design or reading code (e.g., Java, C++, Python). • Experience in SecOps product offerings (e.g., SIEM, SOAR) and the broader vendor space in cybersecurity. • Ability to communicate in English and Spanish fluently to engage with local stakeholders. Preferred qualifications • Experience in security operations, security architecture, or security engineering. • Experience in the implementation and ongoing oversight of SIEM and SOAR deployments. • Familiarity with AI-assisted tools, such as prompt-based threat hunting, automated query translation, natural language investigation, or Agentic AI. • Demonstrated foundational understanding in cloud computing technologies. • Proven track record of success in meeting or exceeding client deliverables and expectations. • Strong client leadership, communication, and people management skills. About the job As a Security Advisor, you will lead strategic enterprise clients across North America and Latin America through modern security transformations. You will guide organizations in maturing their Security Operations, with deep expertise in SIEM and SOAR technologies. As a trusted advisor, you will partner with security leaders to accelerate adoption and drive strategic defense initiatives. You will leverage generative AI and advanced automation to streamline threat detection, investigation, and response, helping clients stay ahead of emerging threats. Responsibilities • Manage a portfolio of Tier 1 global accounts through onboarding and post-onboarding, serving as a trusted advisor to customer executives, driving SaaS Value Realization, and navigating critical client escalations. • Lead detection engineering initiatives and design advanced SOAR automation workflows to transition clients from manual processes to scalable, automated response playbooks. • Architect comprehensive multi-cloud ingestion plans (e.g., GCP) to ensure unified threat visibility and systematically reduce customer security risk. • Guide clients in adopting security capabilities, demonstrating how to leverage generative AI and Agentic Security Operations Center (SOC) workflows to modernize their security posture. • Maintain deep technical expertise through continuous enablement on Google Security Operations (SecOps), Google Threat Intelligence (GTI), Chrome Enterprise Premium (CEP), Cloud Security Posture Management (CSPM) tooling, and GCP architecture to remain at the forefront of cybersecurity trends.

🏢 Summary: Lead the product strategy, roadmap, and launch of Gemini-based, agentic AI customer-support experiences for Google Cloud. The role combines enterprise technical expertise with product leadership to build unified, proactive, and autonomous support solutions and guide stakeholders on their adoption. 🗂️ Requirements: Bachelor’s degree in Computer Science, Information Systems, related technical field, or equivalent practical experience, 9 years of enterprise technical-role experience in technical solutions engineering, software engineering, or technical program management, 9 years of experience in at least two relevant technical domains, 6 years of customer troubleshooting and cloud technical-risk advocacy experience, Ability to read and write code in a general-purpose programming language or perform system design 📃 Skills: Java, C, C++, Python, Shell, Go, JavaScript, Kubernetes, Oracle, SAP, VMWare, Networking, Web, BigData, MachineLearning, SystemsAdministration, Cloud 🏢 Description: Minimum qualifications • Bachelor's degree in Computer Science, Information Systems, related technical field, or equivalent practical experience. • 9 years of experience in a technical role, such as technical solutions engineer, software engineer, or technical program manager, providing enterprise-level support and workflows. • 9 years of experience with two or more of the following: Web Tech, Data/BigData, Systems Admin, Machine Learning, Networking, Kubernetes, Oracle, SAP, VMWare. • 6 years of experience troubleshooting and advocating for customers, addressing Cloud technical risks. • Experience writing and reading code in a general-purpose coding language, such as Java, C, C++, Python, Shell, Go, or JavaScript, or experience in system design. Preferred qualifications • Experience using analytics and data to problem-solve, collaborate, and communicate with stakeholders. • Experience building and understanding agentic AI, large language models (LLMs), and their application in customer-facing products. • Experience launching successful products or services from conception to launch. • Experience developing and managing technical documentation, runbooks, or knowledge bases. About the job The Google Cloud Platform team helps customers transform and build what’s next for their business using cloud technology. Its products are developed for security, reliability, and scalability, running the full stack from infrastructure to applications, devices, and hardware. As a Product Technology Manager for Support on Gemini, you will define and execute the product strategy for a new generation of customer-support experiences, treating support as a product itself. You will bring agentic systems to life to deliver proactive and reactive customer support and help shape the GenAI-driven future of customer interaction and support. Responsibilities • Translate business objectives and requirements from systems program managers into a product idea, strategy, and roadmap for Support on Gemini, aligned with company objectives and customer needs. • Drive the conceptualization, development, and launch of innovative agentic AI systems for customer support, transforming support from fragmented and human-driven to unified, autonomous, and AI-driven. • Own product requirements for Cloud Support technical solutions and collaborate with GCBP, technology vendors, and GCP Product and Engineering to bring new support experiences and features to market. • Act as a subject-matter expert on technical knowledge for the support organization; provide technical guidance and training; and identify and advocate for capabilities and improvements based on support needs and data analysis. • Engage executive leadership and key stakeholders to communicate product strategy, progress, and results.

🏢 Summary: Technical leadership role managing a team that builds capacity-planning systems for high-throughput cloud storage products and large AI/ML workloads. The position owns strategy and delivery for distributed infrastructure solutions, network optimization, automated capacity adjudication, and cross-functional supply alignment. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8 years of software development experience, 3 years of experience with large-scale infrastructure, distributed systems, networks, compute technologies, storage, or hardware architecture, 3 years of technical leadership experience, 2 years of people management or team leadership experience 📃 Skills: Software, Infrastructure, DistributedSystems, Networks, Compute, Storage, Hardware, CapacityPlanning, AI, ML 🏢 Description: Minimum qualifications • Bachelor’s degree, or equivalent practical experience. • 8 years of experience in software development. • 3 years of experience developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture. • 3 years of experience in a technical leadership role. • 2 years of experience in a people management or team leadership role. Preferred qualifications • Master's degree or PhD in Computer Science or a related technical field. • 3 years of experience working in a complex, matrixed organization. • Strong understanding of AI/ML frameworks. • Experience mentoring executive engineers and other technical leads. • Experience in capacity planning for complex, large-scale distributed systems. About the job Responsibilities • Manage team staffing and career growth, uphold a high-performance bar, and foster an environment to build capacity-planning solutions for high-throughput GCS products. • Own the strategy, scoping, navigation, and outcomes for capacity-planning systems targeting high-throughput scenarios, such as the Bandwidth Highway and Rapid Cache. • Guide the team through ambiguity by breaking down complex challenges, including supply scarcity and dense AI zone typologies, into tractable technical milestones. • Navigate complex relationships across GCS, Networking, Compute, and Data Center teams to align supply agendas and ensure seamless onboarding for massive AI/ML workloads. • Drive engineering efforts to automate capacity adjudication, optimize network resources, and accelerate the time required to onboard new high-throughput customers.

🏢 Summary: Senior Performance Co-Design Engineer role focused on analyzing and optimizing LLM serving performance on custom ML accelerators. The position develops simulation, profiling, and modeling tools, partners across hardware and software teams, and informs future TPU and cloud silicon architecture decisions. 🗂️ Requirements: Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, related field, or equivalent practical experience, 5 years of experience in performance modeling, performance engineering, computer architecture, co-design, or systems engineering, C++ or Python programming experience 📃 Skills: C++, Python, Modeling, Architecture, Codesign, Simulation, Profiling, LLMs, TPU 🏢 Description: Minimum qualifications • Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, a related field, or equivalent practical experience. • 5 years of experience in performance modeling/engineering, computer architecture, co-design, or systems engineering. • Experience programming in C++ or Python. Preferred qualifications • Master's degree or PhD in Electrical Engineering, Computer Engineering, or Computer Science, with an emphasis on computer architecture. • Experience with hardware/software co-design problems, especially performance analysis and identification at the pre-silicon stage. • Experience enabling and optimizing large-scale ML models, such as LLMs and large embedding models. • Experience with ML infrastructure, profiling tools, or deep learning inference/serving optimizations. • Familiarity with accelerator architectures. Description Google Cloud’s mission is to make every business successful through AI by combining cutting-edge technology, infrastructure, and talent. AI/ML software engineers in Cloud bridge the gap between pioneering models and a massive product vehicle reaching billions. Our talent density and AI-powered tools drive rapid development, rooted in a culture of empowerment and a bias to action. The TPU Chip Architecture and Performance Co-design team is at the forefront of optimizing custom AI silicon for next-generation machine learning models. As a Senior Performance Co-Design Engineer, you will focus on conducting LLM serving studies. You will analyze and optimize the serving performance of emerging models and use cases on custom hardware, and work closely with hardware architects to influence the evolution of custom ML accelerators. The AI and Infrastructure team delivers AI and Infrastructure at scale, efficiency, reliability, and velocity. Customers include Googlers, Google Cloud customers, and billions of Google users worldwide. Teams work across software and hardware, including TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and more. Responsibilities • Conduct comprehensive serving performance studies on current and emerging LLMs, including 1P and 3P models. • Develop and maintain advanced simulation, profiling, and modeling tools to identify bottlenecks, understand key characteristics, and project serving workload performance. • Partner with model researchers and software and hardware teams to co-design architectural improvements tailored to LLM inference latency and throughput. • Drive data-backed decisions that influence the roadmap for future TPU and Cloud Silicon architectures.

🏢 Summary: Lead the technical direction and end-to-end delivery of AutoCloud Agentic Systems. The role focuses on Generative AI, scalable software development, engineering best practices, and cross-functional alignment to deliver customer value. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8 years of software development experience, 5 years of leadership, people management, hiring, mentoring, and talent-retention experience across global locations, 2 years of Generative AI experience 📃 Skills: GenerativeAI, Softwaredevelopment, AI, Prototyping, Deployment, Monitoring 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 8 years of experience with software development. • 5 years of experience in leadership, people management, hiring, mentoring, and retaining talent across global locations. • 2 years of experience with Generative AI. Preferred qualifications • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • 5 years of experience working in a complex, matrixed organization. About the job Responsibilities • Lead the technical goal and execution for AutoCloud Agentic Systems, ensuring alignment with product goals and user needs. • Drive the end-to-end development life cycle of features, from ideation and prototyping to deployment, monitoring, and iteration, ensuring high quality, scalability, and performance. • Develop technology strategy and phased plans alongside product to drive product improvements or process simplifications. • Partner with cross-functional leaders across Google Cloud and AutoCloud to drive alignment and deliver customer value. • Define and advocate for best practices in AI development and software engineering, ensuring robust and reliable systems.

🏢 Summary: Software engineering role focused on building and optimizing secure, multi-tenant file and block storage capabilities for a distributed cloud environment. The position covers large-scale infrastructure, storage performance benchmarking, and reliability through root-cause remediation and comprehensive testing. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 2 years of programming experience in C++, Go, or Python, 2 years of experience testing, maintaining, or launching software products, 1 year of experience in software design and architecture, 2 years of experience developing large-scale infrastructure, distributed systems, networks, compute technologies, or cloud storage, Experience with cloud compute platforms, including Kubernetes or Cloud Functions 📃 Skills: C++, Go, Python, Kubernetes, CloudFunctions, ONTAP, SVMs, RBAC, IOPS, Benchmarking, Optimization, Golang, Containers 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 2 years of experience programming in C++, Go, or Python. • 2 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture. • 2 years of experience developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies or cloud storage. • Experience with cloud compute platforms such as Kubernetes and Cloud Functions. Preferred qualifications • Master’s degree or PhD in Computer Science or a related technical field. • Experience with systematic performance benchmarking and optimization. • Experience with Kubernetes or container orchestration frameworks. • Experience developing accessible technologies. • Experience in Golang. About the job Software engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information. Products operate at massive scale and extend beyond web search. Engineers work on projects critical to business needs, with opportunities to switch teams and projects as the business evolves. The role requires versatility, leadership, and enthusiasm for solving new full-stack problems across areas such as information retrieval, distributed computing, large-scale system design, networking, data storage, security, artificial intelligence, natural language processing, UI design, and mobile. The Google Distributed Cloud Storage Everywhere team builds storage solutions that enable applications to run seamlessly across data centers, edge environments, and the cloud. Google Cloud delivers enterprise-grade solutions and tools that help developers build more sustainably. Responsibilities • Address and resolve complex issues through the Root-Cause/Remediation (RCR) process, including identifying and closing test gaps with unit, integration, and chaos testing. • Implement secure, isolated storage environments for multiple tenants using Open Network Technology for Appliance Products (ONTAP) Storage Virtual Machines (SVMs) and Role-Based Access Control (RBAC). • Design, develop, and integrate core file and block storage features and management within the Google Distributed Cloud Hosted (GDCH) ecosystem. • Define, measure, and optimize storage performance to meet stringent input/output operations per second (IOPS), throughput, and latency requirements, using Google Cloud best practices and frontline intelligence operations for comprehensive benchmarking and performance characterization.

🏢 Summary: Lead Google Cloud AI Research engineering teams developing and deploying large-scale generative AI solutions. The role combines technical strategy, ML infrastructure optimization, system design, code development, and people leadership across multiple teams and locations. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8+ years of software development experience, 5+ years leading ML design and ML infrastructure optimization, 3+ years in technical leadership, 2+ years with state-of-the-art GenAI techniques or related concepts, 2+ years of people management or team leadership experience 📃 Skills: Python, C, C++, Java, JavaScript, ML, GenAI, LLMs, Multimodal, Vision, Deployment, Evaluation, Debugging, Finetuning 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript). • 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). • 3 years of experience in a technical leadership role. • 2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision). • 2 years of experience in a people management or team leadership role. Preferred qualifications • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • 3 years of experience working in an organization involving cross-functional or cross-business projects. About the job Software Engineering Managers provide technical leadership for major projects while managing teams of engineers. They manage project goals, contribute to product strategy, develop their teams, and help engineers optimize their code. This role manages engineers across multiple teams and locations, a large product budget, and the deployment of large-scale projects across multiple international sites. The Google Cloud AI Research team addresses AI challenges across industries including technology, healthcare, finance, and retail, conducting research with scientific and real-world impact and collaborating with product teams to bring innovations to customers. Responsibilities • Set and communicate team priorities that support broader organizational goals; align strategy, processes, and decision-making across teams. • Set clear expectations based on individuals’ levels and roles; meet regularly to discuss performance and development, and provide feedback and coaching. • Develop the mid-term technical vision and roadmap for one or more teams; evolve the roadmap for future requirements and infrastructure needs. • Design, guide, and vet system designs; write product or system development code to solve ambiguous problems. • Lead the design of GenAI solutions, optimize ML infrastructure, and guide data preparation and model optimization strategies.

🏢 Summary: Technical role focused on building AI-driven financial experiences by integrating third-party tools and agent workflows into an AIX orchestration layer. The position develops scalable, low-latency Generative UI capabilities and personalized financial insights using user signals, while leading architecture and delivery from discovery through production. 🗂️ Requirements: Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience, 5 years of software development experience, Experience with C++, Java, Kotlin, Python, or another general-purpose programming language, Experience developing, prompt-tuning, fine-tuning, or orchestrating LLM and generative AI systems, Experience with algorithms, Experience architecting backend or infrastructure systems 📃 Skills: C++, Java, Kotlin, Python, LLMs, AI, Algorithms, Backend, Infrastructure, MCP, MaRS, Agency, GenUI 🏢 Description: Minimum qualifications: • Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience. • 5 years of software development experience in one or more general-purpose programming languages (e.g., C++, Java, Kotlin, Python). • Experience developing with, prompt-tuning, fine-tuning, or orchestrating Large Language Models (LLMs) and generative AI systems. • Experience with algorithms and architecting backend or infrastructure systems. Preferred qualifications: • Experience with tool execution pipelines, agentic workflows, function calling, or Model Context Protocol (MCP) integration. • Experience working with Generative UI pipelines, adaptive design architectures, or dynamic component rendering systems. • Familiarity with Google Search Next infrastructure, specifically MaRS, Agency, and GenUI ecosystem components. • High interest in personal finance, market intelligence, fintech, or complex transactional domains where high precision and factuality are paramount. Responsibilities: • Lead technical execution for connecting external third-party tools and partner agents into an AIX orchestration layer utilizing the Model Context Protocol (MCP). • Build scalable, low-latency Generative UI capabilities on top of Core Search Next platforms, including MaRS, Agency, and the GenUI framework, to transform raw financial output into actionable, interactive user experiences. • Integrate Zero-Party (0P), First-Party (1P), and Third-Party (3P) user signals to deliver tailor-made financial insights while setting new standards for strict factuality, multi-turn conversation context, and high-utility helpfulness. • Identify engineering gaps, set technical roadmap priorities, and guide initiatives from initial discovery through production deployment. • Build strong relationships with cross-functional partners in Product Management, User Experience, Research, Quality, and External Partner Integration to align technical goals with product strategy.