📍 Job Overview

Job Title: Customer Engineer, Digital Native, Google Cloud (English, Korean)
Company: Google
Location: Seoul, South Korea
Job Type: On-site
Category: Technical Sales & Customer Success
Date Posted: June 24, 2025
Experience Level: 5-10 years
Remote Status: On-site

🚀 Role Summary

Technical Sales & Customer Success: Differentiate Google Cloud to customers, understand their business and technical requirements, and present practical solutions.
Cloud & AI Expertise: Leverage cloud native architecture, generative AI, and machine learning solutions to solve customer challenges.
Customer Engagement & Support: Establish trust as a technical advisor, qualify business opportunities, and resolve technical blockers.
Collaboration & Communication: Work with cross-functional teams, understand customer needs, and present creative solutions effectively.

📝 Enhancement Note: This role requires a strong balance of technical depth in cloud and AI, along with exceptional communication skills to engage customers and drive adoption of Google Cloud solutions.

💻 Primary Responsibilities

Customer Engagement & Solutioning:
- Understand customer business and technical requirements.
- Develop and present creative cloud solutions and architectures to address customer challenges.
- Engage in proofs of concept and troubleshoot technical questions and roadblocks.
Technical Sales Support:
- Identify and qualify business opportunities, understanding customer technical objections.
- Develop strategies to resolve technical blockers and support bid responses.
- Partner with product management to prioritize solutions impacting customer adoption to Google Cloud.
Customer Success & Trust Building:
- Establish trust as a technical advisor, influencing customer technology and business decisions.
- Travel to customer sites, conferences, and other events as needed to build and maintain customer relationships.

📝 Enhancement Note: This role requires a high level of customer focus, with a strong emphasis on understanding customer needs and providing tailored, value-driven solutions.

🎓 Skills & Qualifications

Education: Bachelor's degree or equivalent practical experience in Computer Science, Engineering, or a related field.

Experience: 4+ years of experience in cloud native architecture, with a strong focus on generative AI, machine learning, and data analytics solutions.

Required Skills:

Cloud native architecture and infrastructure management.
Generative AI, including Large Language Models (LLMs), multi-modal models, and leveraging frameworks.
Machine learning model development and deployment frameworks (e.g., PyTorch, TensorFlow, Jax, Ray).
AI accelerators (e.g., TPUs, GPUs) and using machine learning APIs.
Data and information management, big data, and AI trends.
Architecting and developing software or infrastructure for distributed systems.
Excellent communication skills in English and Korean, with the ability to present technical solutions to both technical stakeholders and executive leadership.

Preferred Skills:

Experience in building machine learning solutions and leveraging specific machine learning architectures (e.g., deep learning, LSTM, convolutional networks).
Experience in architecting and developing software or infrastructure for distributed systems.
Ability to learn, understand, and work with emerging technologies, methodologies, and solutions in the Cloud/IT Technology space.

📝 Enhancement Note: This role requires a strong blend of technical depth in cloud and AI, along with exceptional communication skills and the ability to build and maintain customer relationships.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate a strong understanding of cloud native architecture, generative AI, and machine learning solutions through relevant projects and case studies.
Showcase your ability to present technical solutions and their business value to both technical stakeholders and executive leadership.
Highlight your experience in architecting and building ML/DA solutions, including data pipelines, ML pipelines, model training, and serving infrastructure.

Technical Documentation:

Document your approach to solving complex technical problems, including data management, AI, and distributed systems.
Showcase your ability to collaborate with cross-functional teams and understand customer needs.
Demonstrate your understanding of emerging technologies, methodologies, and solutions in the Cloud/IT Technology space.

📝 Enhancement Note: As this is a customer-facing role, a well-curated portfolio demonstrating your ability to understand and address customer needs is essential.

💵 Compensation & Benefits

Salary Range: Based on market research and industry standards, the estimated salary range for this role in Seoul, South Korea is ₩80,000,000 - ₩120,000,000 per year. This range takes into account the candidate's experience level, the company's size, and the region's cost of living.

Benefits:

Competitive compensation and benefits package.
Generous vacation and time-off policies.
Opportunities for professional development, training, and career growth.
A dynamic and innovative work environment, with a focus on collaboration and teamwork.

Working Hours: Full-time position, with standard working hours Monday through Friday, 9:00 AM to 6:00 PM. Occasional travel may be required to visit customer sites, conferences, and other events.

📝 Enhancement Note: Salary estimates are based on regional market research and industry standards for similar roles at Google. Benefits information is based on Google's standard employee benefits package.

🎯 Team & Company Context

🏢 Company Culture

Industry: Google operates in the technology industry, with a focus on cloud computing, AI, and machine learning solutions. As a customer engineer, you will work at the intersection of these technologies to drive customer adoption and success.

Company Size: Google is a large, multinational corporation with a significant presence in the technology industry. As a customer engineer, you will have the opportunity to work with a diverse and talented team, with access to extensive resources and support.

Founded: Google was founded in 1998 by Larry Page and Sergey Brin. The company has since grown to become a global leader in technology, with a strong focus on innovation and continuous learning.

Team Structure:

The customer engineering team works closely with technical sales teams to differentiate Google Cloud to customers and assist in solving their business challenges.
The team is responsible for understanding customer technical objections and developing strategies to resolve technical blockers.
Customer engineers work with customers to demonstrate and prototype Google Cloud integrations, and recommend integration strategies, architectures, platforms, and application infrastructure required to implement a complete solution using best practices on Google Cloud.

Development Methodology:

Google Cloud follows Agile development methodologies, with a focus on iterative development, continuous integration, and collaboration.
Customer engineers work closely with product management to prioritize solutions impacting customer adoption to Google Cloud.
The team uses a variety of tools and technologies to support their work, including Google Workspace, Google Cloud Platform, and other third-party tools.

Company Website: Google Cloud

📝 Enhancement Note: Google's company culture is characterized by a strong focus on innovation, collaboration, and continuous learning. As a customer engineer, you will have the opportunity to work with a diverse and talented team, with access to extensive resources and support.

📈 Career & Growth Analysis

Web Technology Career Level: This role is a senior-level position, requiring a strong blend of technical depth in cloud and AI, along with exceptional communication skills and the ability to build and maintain customer relationships.

Reporting Structure: Customer engineers report directly to the customer engineering manager and work closely with technical sales teams to differentiate Google Cloud to customers and assist in solving their business challenges.

Technical Impact: In this role, you will have a significant impact on customer adoption and success, driving the use of Google Cloud solutions to address their business challenges. You will work closely with customers to understand their requirements and present practical solutions on Google Cloud.

Growth Opportunities:

Technical Growth: Deepen your expertise in cloud native architecture, generative AI, and machine learning solutions, and stay up-to-date with emerging technologies and trends in the Cloud/IT Technology space.
Leadership Growth: Develop your leadership skills by mentoring junior team members, driving technical initiatives, and influencing customer technology and business decisions.
Career Progression: As a senior-level role, this position offers opportunities for career progression, such as moving into a leadership role or taking on more complex customer engagements.

📝 Enhancement Note: This role offers significant opportunities for technical and leadership growth, as well as career progression. As a senior-level position, it provides a strong foundation for continued success in the technology industry.

🌐 Work Environment

Office Type: Google's offices are designed to foster collaboration and innovation, with a focus on open workspaces, breakout areas, and amenities to support employee well-being and productivity.

Office Location(s): Seoul, South Korea. The office is located in the heart of the city, with easy access to public transportation and nearby amenities.

Workspace Context:

Collaboration: The office is designed to encourage collaboration and teamwork, with open workspaces, breakout areas, and meeting rooms to support team meetings and brainstorming sessions.
Technology: Customer engineers have access to the latest hardware, software, and tools to support their work, including Google Workspace, Google Cloud Platform, and other third-party tools.
Flexibility: The office offers flexible work arrangements, with a focus on results and productivity rather than strict working hours.

Work Schedule: Full-time position, with standard working hours Monday through Friday, 9:00 AM to 6:00 PM. Occasional travel may be required to visit customer sites, conferences, and other events.

📝 Enhancement Note: Google's work environment is designed to foster collaboration, innovation, and employee well-being. As a customer engineer, you will have access to extensive resources and support to help you succeed in your role.

📄 Application & Technical Interview Process

Interview Process:

Technical Phone Screen (60 minutes): Discuss your experience with cloud native architecture, generative AI, and machine learning solutions. Solve technical problems and present your approach to solving complex customer challenges.
Technical Deep Dive (90 minutes): Dive deeper into your technical expertise, focusing on your experience with cloud native architecture, generative AI, and machine learning solutions. Present a case study demonstrating your ability to understand and address customer needs.
Behavioral Interview (60 minutes): Discuss your approach to customer engagement, problem-solving, and collaboration. Share examples of your ability to build and maintain customer relationships and drive customer success.
Final Interview (60 minutes): Meet with the hiring manager and other stakeholders to discuss your fit for the role, your long-term career goals, and your vision for driving customer adoption and success.

Portfolio Review Tips:

Case Studies: Prepare case studies demonstrating your ability to understand and address customer needs, with a focus on cloud native architecture, generative AI, and machine learning solutions.
Technical Deep Dive: Be prepared to discuss your approach to solving complex technical problems, including data management, AI, and distributed systems.
Customer Engagement: Highlight your ability to build and maintain customer relationships, with a focus on understanding customer needs and presenting practical solutions.

Technical Challenge Preparation:

Cloud Native Architecture: Brush up on your knowledge of cloud native architecture, with a focus on generative AI, machine learning, and data analytics solutions.
AI & Machine Learning: Review your understanding of AI and machine learning, including model development, deployment, and serving infrastructure.
Customer Engagement: Prepare for questions about your approach to customer engagement, problem-solving, and collaboration.

ATS Keywords: [Cloud Native Architecture, Generative AI, Machine Learning, Data Analytics, Customer Engagement, Technical Sales, Problem-Solving, Collaboration, Cloud Solutions, AI Accelerators, Distributed Systems, Emerging Technologies, Technical Presentation, Customer Success]

📝 Enhancement Note: The interview process for this role is designed to assess your technical depth in cloud and AI, along with your ability to engage customers and drive their success. Be prepared to discuss your approach to solving complex customer challenges and demonstrate your ability to build and maintain customer relationships.

🛠 Technology Stack & Web Infrastructure

Cloud Platform: Google Cloud Platform (GCP)

Cloud Native Architecture:

Kubernetes
Docker
Microservices
Serverless (e.g., Cloud Functions, Cloud Run)
Infrastructure as Code (IaC) tools (e.g., Terraform, Cloud Deployment Manager)

Generative AI & Machine Learning:

Large Language Models (LLMs)
Multi-modal models
Leveraging frameworks (e.g., Hugging Face, TensorFlow, PyTorch)
AI accelerators (e.g., TPUs, GPUs)
Machine learning APIs (e.g., AI Platform, AutoML)

Data Analytics & Management:

BigQuery
Cloud Storage
Cloud Pub/Sub
Cloud Dataflow
Cloud DataProc
Cloud Composer

Collaboration & Productivity Tools:

Google Workspace (G Suite)
Slack
Jira
Confluence

📝 Enhancement Note: As a customer engineer, you will work with a wide range of technologies, including cloud native architecture, generative AI, and machine learning solutions. Familiarize yourself with the Google Cloud Platform and the tools and technologies used to support customer success.

👥 Team Culture & Values

Google's Core Values:

User-centric: Focus on understanding and addressing customer needs to drive their success.
Innovation: Embrace a culture of continuous learning and improvement.
Collaboration: Work together to achieve common goals and drive customer adoption and success.
Inclusion: Foster a diverse and inclusive work environment, where everyone can contribute and thrive.

Customer Engineering Team Values:

Customer focus: Understand and address customer needs to drive their success.
Technical excellence: Demonstrate a deep understanding of cloud native architecture, generative AI, and machine learning solutions.
Collaboration: Work closely with technical sales teams and other stakeholders to drive customer adoption and success.
Problem-solving: Approach complex customer challenges with a solutions-oriented mindset, focusing on understanding and addressing customer needs.

Collaboration Style:

Cross-functional collaboration: Work closely with technical sales teams, product management, and other stakeholders to drive customer adoption and success.
Peer-to-peer learning: Share knowledge and expertise with team members to drive continuous learning and improvement.
Customer-centric approach: Focus on understanding and addressing customer needs to drive their success.

📝 Enhancement Note: Google's company culture is characterized by a strong focus on innovation, collaboration, and continuous learning. As a customer engineer, you will have the opportunity to work with a diverse and talented team, with access to extensive resources and support.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Cloud Native Architecture: Stay up-to-date with the latest trends and best practices in cloud native architecture, generative AI, and machine learning solutions.
Customer Engagement: Develop your ability to understand and address customer needs, with a focus on presenting practical solutions that drive their success.
Emerging Technologies: Keep pace with the rapid evolution of cloud and AI technologies, and be prepared to adapt your approach to solving customer challenges as new tools and techniques emerge.

Learning & Development Opportunities:

Technical Training: Participate in technical training and certification programs to deepen your expertise in cloud native architecture, generative AI, and machine learning solutions.
Conferences & Events: Attend industry conferences and events to stay up-to-date with the latest trends and best practices in cloud and AI technologies.
Mentorship: Seek out mentorship opportunities to develop your leadership skills and drive your career growth.

📝 Enhancement Note: As a customer engineer, you will face a wide range of technical challenges, with a strong focus on understanding and addressing customer needs. Be prepared to adapt your approach to solving customer challenges as new tools and techniques emerge, and seek out opportunities for continuous learning and growth.

💡 Interview Preparation

Technical Questions:

Cloud Native Architecture: Be prepared to discuss your approach to cloud native architecture, with a focus on generative AI, machine learning, and data analytics solutions.
AI & Machine Learning: Review your understanding of AI and machine learning, including model development, deployment, and serving infrastructure.
Customer Engagement: Prepare for questions about your approach to customer engagement, problem-solving, and collaboration.

Company & Culture Questions:

Google's Core Values: Familiarize yourself with Google's core values and be prepared to discuss how you embody them in your work.
Customer Engineering Team Values: Understand the customer engineering team's values and be prepared to discuss how you align with them in your approach to customer success.
Customer-centric Approach: Be prepared to discuss your approach to understanding and addressing customer needs, with a focus on driving their success.

Portfolio Presentation Strategy:

Case Studies: Prepare case studies demonstrating your ability to understand and address customer needs, with a focus on cloud native architecture, generative AI, and machine learning solutions.
Technical Deep Dive: Be prepared to discuss your approach to solving complex technical problems, including data management, AI, and distributed systems.
Customer Engagement: Highlight your ability to build and maintain customer relationships, with a focus on understanding customer needs and presenting practical solutions.

📝 Enhancement Note: The interview process for this role is designed to assess your technical depth in cloud and AI, along with your ability to engage customers and drive their success. Be prepared to discuss your approach to solving complex customer challenges and demonstrate your ability to build and maintain customer relationships.

📌 Application Steps

To apply for this customer engineer position at Google:

Submit your application through the application link: Google Careers - Customer Engineer, Digital Native, Google Cloud (English, Korean)
Prepare your portfolio with live demos and responsive examples: Focus on case studies demonstrating your ability to understand and address customer needs, with a focus on cloud native architecture, generative AI, and machine learning solutions.
Optimize your resume for web technology roles: Highlight your experience with cloud native architecture, generative AI, machine learning, and data analytics solutions, with a focus on customer success and technical sales.
Prepare for technical interviews: Brush up on your knowledge of cloud native architecture, generative AI, and machine learning solutions, and be prepared to discuss your approach to solving complex customer challenges.
Research Google's company culture: Familiarize yourself with Google's core values and the customer engineering team's values, and be prepared to discuss how you align with them in your approach to customer success.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web technology industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Customer Engineer, Digital Native, Google Cloud (English, Korean)