Customer Engineer, Data Analytics and AI, Google Cloud - Singapore

GOOGLE ASIA PACIFIC PTE. LTD.; Singapore; On-site; SGD 120,000 - 150,000; Full time

Job summary

A leading global technology company in Singapore is seeking a Customer Engineer. This role involves collaborating with sales teams as an expert in data analytics and AI, showcasing Google Cloud solutions. Responsibilities include designing data lifecycle solutions and guiding customers in AI integration. Candidates should possess a bachelor's degree, 10 years of experience in cloud architecture, and familiarity with AI/ML frameworks. The position offers the opportunity to work in a dynamic environment with cutting-edge technology.

Qualifications

• 10 years of experience in a customer-facing or support role.
• Experience with AI/ML lifecycle and frameworks.
• Experience in data warehouses and data governance.

Responsibilities

• Design and implement solutions covering the entire data lifecycle.
• Guide customers in integrating collaborative AI agents.
• Communicate architectural concepts to stakeholders.

Skills

Cloud native architecture experience

AI/ML practical application

Data processing (ETL/ELT)

Solution architecture

Communication skills

Education

Bachelor's degree or equivalent

Tools

TensorFlow

PyTorch

Job description

Product area

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.

Job description

The Google Cloud Platform team helps customers transform and build what’s next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes that use technology to connect with customers, employees and partners.

Additional job description

As a Customer Engineer, you will collaborate with technical sales teams as a data analytics and Artificial Intelligence expert to showcase Google Cloud’s value. You will help customers and partners leverage Google Cloud by designing solutions, conducting proofs‑of‑concept and resolving technical issues related to data migrations and lifecycle management. You will understand customer needs, present tailored solutions and demonstrate technical and communication skills while working with a team of Googlers that fosters equal opportunities for success.

Qualifications

Job responsibilities

• Design and implement solutions that cover the entire data lifecycle from ingestion, storage and processing in both batch and real‑time to advanced analytics and Machine Learning (ML) model deployment.
• Guide customers in building and integrating collaborative AI agents using tools like Vertex AI agent engine and Agent Development Kit (ADK) and understand the Agent2Agent protocol can facilitate seamless communication and data exchange between these agents across systems.
• Identify opportunities where AI agents can automate tasks, enhance decision‑making and create value, ensuring solutions are technically sound and deliver tangible business outcomes.
• Communicate architectural concepts effectively to technical stakeholders and executive leadership, demonstrating Google Cloud’s data and AI offerings address and unlock new possibilities.
• Leverage the latest advancements in Google Cloud’s data and AI portfolio to provide solutions and competitive differentiation.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.
• 10 years of experience with cloud native architecture in a customer‑facing or support role.
• Experience with practical application and architectural considerations of AI/ML, including Machine Learning (ML) lifecycle, ML frameworks (e.g., TensorFlow, PyTorch) and MLOps principles.
• Experience in developing data warehouses, data lakes, batch/real‑time event processing, streaming, data processing (ETL/ELT), data migrations, data visualization and data governance on cloud native architectures.
• Experience in conducting technical discovery, business and technical requirements and translating them into efficient and innovative technical architectures that leverage data and AI services.

Preferred qualifications

• Experience implementing MLOps best practices, CI/CD pipelines for ML models and infrastructure as code for deploying data and AI solutions.
• Experience in integrating data and AI solutions with existing enterprise systems, on‑premises infrastructure and third‑party applications.
• Experience in optimizing performance, cost‑efficiency and scalability of large‑scale data processing pipelines and ML inference systems.
• Experience with hybrid cloud architectures and multi‑cloud strategies, particularly in data integration and migration.
• Experience with architectural design and implementation of solutions involving LLMs, Generative AI models or AI agents (e.g., Vertex AI Agent Engine, ADK, LangChain, LlamaIndex).