Prototyping Customer Engineer, Data
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Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Singapore; Bengaluru, Karnataka, India; Gurugram, Haryana, India; Mumbai, Maharashtra, India.Minimum qualifications:
- Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
- 10 years of experience in cloud computing, with a focus on Artificial Intelligence/Machine Learning (AI/ML), data analytics, and data engineering.
- Experience with modern application development and Developer Operations (DevOps) practices, including Continuous Integration/Continuous Deployment (CI/CD), containerization (Docker, Kubernetes), and infrastructure-as-code.
- Experience in programming languages such as Python with developing and deploying Generative Artificial Intelligence (GenAI) models and applications.
- Experience with data analysis, data engineering, database technologies (SQL, NoSQL), and data warehousing solutions.
- Ability to analyze business problems and develop technical solutions.
Preferred qualifications:
- 10 years of experience in cloud computing, with AI/ML, data analytics, and data engineering, in a customer-facing or consulting role.
- Experience in architecting and developing software or infrastructure for scalable, distributed systems, particularly those related to AI/ML workloads.
- Experience in understanding customer requirements and designing technical architectures to meet needs.
- Experience in building prototypes and proof-of-concepts to demonstrate solutions.
- Experience in managing stakeholder expectations and building consensus around technical projects.
- Knowledge of cloud services related to AI/ML, data analytics, and data engineering.
About the job
When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.
The Asia Pacific (APAC) Solutions Prototyping Team partners with customers to bring their goals to life. We collaborate to understand tests and ideas, then design and build practical working prototypes using data, analytics, AI, and software engineering. Our goal is to demonstrate how these technologies can work together to achieve impactful business results.
In this role, you will lead the design and development of prototypes, demonstrating the transformative power of data, analytics, AI, and software engineering to solve business tests for customers. You will mentor team members and contribute to the direction of our prototyping efforts.
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.
Responsibilities
- Lead the design, development, and iterative refinement of data-centric and Artificial Intelligence (AI) powered prototypes on Google Cloud Platform (GCP), showcasing the potential of data and AI to address specific business needs.
- Collaborate with customers to understand their business tests, technical requirements, and objectives. Build relationships with customers and stakeholders.
- Mentor and guide junior team members, fostering a culture of innovation and learning.
- Contribute to the development of internal best practices and methodologies for data and AI-motivated solutions.
- Stay up-to-date with emerging trends and technologies in cloud computing, data science and AI/ML, and identify opportunities for their application in prototyping projects.
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