Google

Runs Search and YouTube and builds Gemini AI

Technical Success Account Manager - Alphabet Bets AI Infrastructure, Google Cloud

Implementation & Technical Account ManagementPosted on Nov 12

Full-time

About the Job

Requirements

A bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
10 years of experience in a customer-facing role working with stakeholders and managing technical implementations or transformation programs.
Experience with cloud computing and enterprise architecture principles, including Kubernetes (GKE), GPU/compute infrastructure, networking, security, Infrastructure-as-Code (IaC), cloud-native operations, and observability frameworks in production environments.
Experience presenting to technical and executive stakeholders.

Responsibilities

Establish and lead technical governance, focusing on platform health metrics, capacity forecasting, and continuous GPU/TPU/compute cost optimization.
Provide technical guidance and lead the adoption of GKE multi-cluster architecture, Infrastructure-as-Code (IaC), and scheduling best practices via in-depth search and workshops.
Drive platform stability and operational excellence through deep architectural and resilience health assessments across massive-scale GPU and TPU supercomputing fleets.
Serve as the strategic technical advisor and escalation lead to resolve critical reliability concerns, high-severity incidents, and hardware/OEM anomalies for business-critical AI workloads.
Act as the internal customer advocate, translating technical obstacles to influence GKE/GCE product roadmaps while owning workload stabilization, SLA tracking, and ongoing optimization.
Serve as a strategic technical leader aligned with Alphabet's flagship AI life-sciences and frontier research organizations.
Drive sustained platform health, achieve technical excellence, and ensure stability for massive-scale GPU and TPU training and batch workloads running on Google Kubernetes Engine (GKE).
Translate complex AI research and compute objectives into technical governance and resilient multi-cluster cloud architectures.
Forge executive relationships, lead adoption of Google Cloud and Kubernetes architecture standards, serve as the primary point of accountability for critical platform issues and proactive risk mitigation, and translate customer needs into Google Cloud's Product and Engineering roadmaps.

Desired Qualifications

A master's degree or MBA in a Management, Technical, or Engineering field, and Cloud professional certifications.
Experience supporting frontier AI/ML training or high-performance computing (HPC) workloads in critical cloud operations domains, including capacity planning, release management, and escalation management procedures.
Experience leading technical governance activities, such as Architecture Review Boards (ARBs), resilience reviews, and developing reference architectures for multi-cluster Kubernetes (GKE, Kueue/MultiKueue) and accelerator fleets.
Experience coordinating cross-functional issue resolution across core product/engineering teams and external hardware OEMs or accelerator vendors, such as NVIDIA.

Establish and lead technical governance, focusing on platform health metrics, capacity forecasting, and continuous GPU/TPU/compute cost optimization.
Provide technical guidance and lead the adoption of GKE multi-cluster architecture, Infrastructure-as-Code (IaC), and scheduling best practices via in-depth search and workshops.
Drive platform stability and operational excellence through deep architectural and resilience health assessments across massive-scale GPU and TPU supercomputing fleets.
Serve as the strategic technical advisor and escalation lead to resolve critical reliability concerns, high-severity incidents, and hardware/OEM anomalies for business-critical AI workloads.
Act as the internal customer advocate, translating technical obstacles to influence GKE/GCE product roadmaps while owning workload stabilization, SLA tracking, and ongoing optimization.

Minimum qualifications:

Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
10 years of experience in a customer-facing role working with stakeholders and managing technical implementations or transformation programs.
Experience with cloud computing and enterprise architecture principles, including Kubernetes (GKE), GPU/compute infrastructure, networking, security, Infrastructure-as-Code (IaC), cloud-native operations, and observability frameworks in production environments.
Experience presenting to technical and executive stakeholders.

Preferred qualifications:

Master's degree or MBA in a Management, Technical, or Engineering field, and Cloud professional certifications.
Experience supporting frontier AI/ML training or high-performance computing (HPC) workloads in critical cloud operations domains, including capacity planning, release management, and escalation management procedures.
Experience leading technical governance activities, such as Architecture Review Boards (ARBs), resilience reviews, and developing reference architectures for multi-cluster Kubernetes (GKE, Kueue/MultiKueue) and accelerator fleets.
Experience coordinating cross-functional issue resolution across core product/engineering teams and external hardware OEMs or accelerator vendors (e.g., NVIDIA).

The Google Kubernetes Engine (GKE) AI Orchestration team builds the foundational scheduling, training, and multi-cluster orchestration platform powering frontier AI research at Google, Alphabet Bets, and global AI leaders. Within ACI Product, our Strategic first-party (1P) and Alphabet Bets Infrastructure program partners directly with Alphabet's flagship AI research organizations to ensure massive GPU and TPU supercomputing fleets operate with maximum goodput, architectural resilience, and operational predictability.

As a Technical Success Account Manager (TSAM) for Alphabet Bets AI Infrastructure within Google Cloud ACI Product, you will serve as a strategic technical leader aligned with Alphabet's flagship AI life-sciences and frontier research organizations. Embedded directly within the core GKE Product and Engineering organization, you are responsible for driving sustained platform health, achieving technical excellence, and ensuring stability for massive-scale GPU and TPU training and batch workloads running on Google Kubernetes Engine (GKE).

You will serve as the partner's trusted technical advisor, translating complex AI research and compute objectives into technical governance and resilient multi-cluster cloud architectures. You will independently forge strong executive relationships, lead the adoption of Google Cloud and Kubernetes architecture standards, act as the primary point of accountability for resolving critical platform issues and proactive risk mitigation, and serve as the internal customer advocate translating needs directly into Google Cloud's Product and Engineering roadmaps.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Poland: zł440000 - zł451000 (PLN) + 20% bonus target + equity + benefits

Learn more about benefits at Google.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Kraków, Poland; Warsaw, Poland.

Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
10 years of experience in a customer-facing role working with stakeholders and managing technical implementations or transformation programs.
Experience with cloud computing and enterprise architecture principles, including Kubernetes (GKE), GPU/compute infrastructure, networking, security, Infrastructure-as-Code (IaC), cloud-native operations, and observability frameworks in production environments.
Experience presenting to technical and executive stakeholders.

About the Company

Google

Runs Search and YouTube and builds Gemini AI

Google runs the world's most used search engine and free services such as YouTube, Android, and Gmail, and it builds the Gemini AI models that work inside them. In 2017, its researchers invented the transformer, the neural network design behind ChatGPT and most other AI chatbots. People use these services without paying, and Google earns most of its money from ads placed beside search results and YouTube videos. Businesses rent computing power and Gemini models through Google Cloud, and Google also sells subscriptions and Pixel phones. Larry Page and Sergey Brin founded Google in 1998 as Stanford PhD students; it is based in Mountain View, California, United States, and is the main business of parent company Alphabet.

Company size: 10,001+
Company stage: IPO
Headquarters: Mountain View, CA
Founded: 1998

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