Customer Engineer, Startups, Google Cloud

🏢 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: Lead global alliances with Global Systems Integrators to expand enterprise adoption and business growth on Google Cloud. The role owns joint business plans, partner offerings and go-to-market initiatives, executive engagement, performance tracking, and cross-functional alignment. 🗂️ Requirements: Bachelor's degree or equivalent practical experience, 15 years of experience in strategy consulting, enterprise sales, or business development, 5 years of experience working with Global Systems Integrators, Experience with enterprise public-cloud solutions and services, Experience designing and building go-to-market models with Global Systems Integrators, Experience managing multiple stakeholders 📃 Skills: Cloud 🏢 Description: Minimum qualifications • Bachelor's degree or equivalent practical experience. • 15 years of experience in strategy consulting, enterprise sales or business development, including 5 years of experience working with Global Systems Integrators (GSI). • Experience with public cloud solutions and services in the enterprise segment. • Experience designing and building go-to-market models with GSIs. • Experience managing multiple stakeholders. Preferred qualifications • MBA or Master's degree in a technical field. • Knowledge of the cloud services landscape and ability to provide industry insights. • Ability to translate data and trends into strategies and compelling messages. • Excellent communication skills and ability to conduct partner CXO engagements. • Excellent leadership and persuasion skills, along with the ability to mentor others. About the job Google Cloud helps organisations empower their employees, serve their customers, and build what’s next for their business with cloud technology. The Global Systems Integrators (GSI) and Consulting Partnerships team manages strategic relationships with top partners. As a Global Alliance Lead, you will help partners scale their worldwide business on Google Cloud. You will act as a trusted advisor throughout the journey of identifying new opportunities, developing capabilities, solutions and service offerings, pursuing go-to-market campaigns, landing wins, and delivering customer success. Responsibilities • Engage with C-level stakeholders, foster relationships between Google leaders, and partner with executives across sales and engineering. • Develop well-thought-out business plans with clear priorities, joint initiatives, and specific goals for growing pipeline, wins, and consumption. • Create compelling offerings and go-to-market initiatives with partners by quantifying opportunities and making a business case for investments as necessary. • Define, track, and analyse performance against specific measures of success for quantifiable, tangible progress. • Collaborate and align with cross-functional stakeholders across both Google and the partner organisation to maximise impact and build a long-term partnership.

🏢 Summary: Lead a newly consolidated engineering team building the technical foundation for safe, scalable Google Cloud use across Alphabet, including AI solutions and infrastructure automation. The role combines people leadership, technical strategy, system design, and hands-on engineering for large-scale, international deployments. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8 years of software development experience, 2 years of people management or team leadership experience, Experience integrating generative AI tools or LLM interfaces into workflows 📃 Skills: SoftwareDevelopment, GenerativeAI, LLMs, Leadership 🏢 Description: Minimum qualifications • Bachelor’s degree, or equivalent practical experience. • 8 years of experience in software development. • 2 years of experience in a people management or team leadership role. • Experience integrating generative AI tools or LLM interfaces into workflows. 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. • Experience or strong interest in building execution runtimes and sandboxes for AI/ML workloads or autonomous agent frameworks (e.g., Jetski, CASG, Vertex Agent Engine). • Experience managing corporate customer migration, intake pipelines, or onboarding workflows at scale. • Familiarity with Google Cloud security products (such as VPC Service Controls and Cloud Firewalls), as well as advanced networking technologies like eBPF network policies, Cilium, and Envoy sidecar proxies. • Familiarity with Google-internal production primitives and data access layers (F1, Spanner). About the job Software Engineering Managers provide technical leadership for major projects while managing teams of engineers. They optimize their own code, enable engineers to optimize theirs, manage project goals, contribute to product strategy, and develop their teams. Teams work across areas including information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, and user interface design. With technical and leadership expertise, you will manage engineers across multiple teams and locations, oversee a large product budget, and lead deployment of large-scale projects across multiple international sites. The Hybrid Cloud Environment (HCE) team enables Alphabet’s safe-by-default use of Google Cloud Platform (GCP) by shifting non-functional requirements—including security, privacy, regulatory, and FinOps—into the platform layer. You will lead a newly consolidated engineering team combining the former Cloud AI Solutions and Corp Run workstreams; the team will support Cloud for Alphabet (C4A) and Project Reef, making “intent become infrastructure.” The Core team builds the technical foundation behind flagship products. The team owns and advocates for underlying design elements, developer platforms, product components, and infrastructure; builds central solutions across products; removes technical barriers; strengthens existing systems; and influences important technical decisions across the organization. Responsibilities • Set and communicate team priorities that support broader organizational goals. • Align strategy, processes, and decision-making across teams. • Set clear expectations for individuals based on their level and role, aligned with organizational goals. • Meet regularly with individuals to discuss performance and development, and provide feedback and coaching. • Develop the mid-term technical outlook and roadmap for one or more teams. • Evolve the roadmap to meet anticipated future requirements and infrastructure needs. • Design, guide, and vet system designs within the broader area, and write product or system development code to solve ambiguous problems. • Review engineers’ code and provide feedback to ensure best practices for style, code check-in, accuracy, testability, and efficiency.

🏢 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: Lead the architecture and scaling of AI/ML infrastructure for YouTube Ads creative automation. The role focuses on high-throughput distributed systems, GenAI media-processing pipelines, experimentation platforms, and technical leadership across product and research teams. 🗂️ Requirements: Bachelor’s degree in Computer Science, related technical field, or equivalent practical experience, 8 years of software development experience, 5 years of software product testing and launch experience, 5 years building large-scale infrastructure, distributed systems, networks, compute, storage, or hardware architecture, 3 years of software design and architecture experience, Experience designing or deploying machine-learning infrastructure or platforms 📃 Skills: Python, TensorFlow, PyTorch, Cloud, Distributed, Infrastructure, Architecture, Algorithms, MachineLearning, DeepLearning, GenAI 🏢 Description: Minimum qualifications • Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience. • 8 years of experience in software development. • 5 years of experience testing and launching software products. • 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture. • 3 years of experience with software design and architecture. • Experience designing or deploying machine learning (ML) infrastructure or platforms. Preferred qualifications • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • 8 years of experience with data structures and algorithms. • 3 years of experience in a technical leadership role leading project teams and setting technical direction. • 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects. • Proficiency in deep learning frameworks (e.g., TensorFlow, PyTorch) and cloud/distributed data technologies. About the job Develop next-generation technologies that operate at massive scale. Work on a project critical to business needs, with opportunities to switch teams and projects as priorities evolve. Bring ideas across areas including distributed computing, large-scale system design, networking, data storage, artificial intelligence, and more. Manage project priorities, deadlines, and deliverables. Design, develop, test, deploy, maintain, and enhance software solutions. The YouTube Ads Creative Optimization (YACO) team develops Creative Automation applications that drive advertiser value with minimal advertiser effort by leveraging AI technologies. The team operates at the intersection of Ads, YouTube, and Research. Responsibilities • Serve as the technical leader responsible for architecting, scaling, and steering next-generation infrastructure that powers AI/ML applications. • Operate at the intersection of Ads, YouTube, and GenAI research to build high-throughput systems enabling seamless creative generation and optimization. • Define the technical roadmap and architect scalable foundational infrastructure, including creative data engines, generation and rendering pipelines, and agentic orchestration frameworks. • Design and optimize distributed systems for complex GenAI and heavy media-processing workloads. • Build and mature experiment and learning infrastructure to accelerate model training, evaluation, and rapid deployment. • Partner with Product Management, Research, and executive leadership to align infrastructure capabilities with long-term business goals. • Guide, mentor, and elevate executive and junior engineers, fostering technical excellence and execution.

🏢 Summary: Lead manufacturing test engineering for hardware systems, managing a team and developing scalable test strategies, automation, and process improvements. The role addresses complex product failures through RCCA, data collection, and manufacturing-process qualification for server, storage, and networking hardware. 🗂️ Requirements: Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent engineering experience, 10 years of test engineering experience in electronics manufacturing, 8 years of people management experience, Python, Bash, and Shell scripting experience for product-specific test plans and test execution 📃 Skills: Python, Bash, Shell, RCCA, ICT, BSCAN 🏢 Description: Minimum qualifications • Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent engineering experience. • 10 years of experience in Test Engineering in electronics manufacturing. • 8 years of experience in people management. • Experience coding in Python, Bash, and Shell scripting to generate product-specific test plans and execute testing accordingly. Preferred qualifications • Experience in manufacturing, quality, or product engineering for hardware technology and systems. • Experience working with server, storage, and networking products, especially AI and ML servers, racks, and integration. • Experience with test station bring-up, gauge R&R/correlation, and partner or agreement manufacturing (ODM, OEM, JDM). • Experience managing manufacturing test hardware using custom electronics, fixturing, instrumentation, and defining test strategy, test automation, test optimization, and scaling test capacity. • Experience with design for test and structural tests such as ICT/BSCAN, Board- and System-level Functional Tests. • Ability to drive improvement of test systems and processes for scaling test capacity. About the job Join a team developing custom silicon solutions that support direct-to-consumer hardware products. Contribute to next-generation hardware experiences focused on performance, efficiency, and integration, while supporting the technical infrastructure behind data centers, platforms, and networks. Responsibilities • Lead a team; set and communicate individual and team priorities that support organizational goals. • Meet regularly with individuals to discuss performance and development, and provide feedback and coaching. • Apply Root Cause Corrective Action (RCCA) fundamentals and collaborate with teams to analyze failures and resolve issues. • Define and execute data-collection activities for highly complex technical issues. • Drive process design, optimization, and qualification activities for manufacturing processes involving components, parts, or products.

🏢 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.

🏢 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: 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: 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.