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Information & Communication Technology 🏢 Full Time ⭐️ Terverifikasi

AI Adoption Customer Engineer - Google Cloud (Bali, Remote)

Google
Bali, Indonesia
Salary Estimate
Rp 450.000.000 – Rp 750.000.000
Newest
Live Update
4 Juli 2026
Deadline
4 Jul 2027

job description

Join Google Cloud as an AI Adoption Customer Engineer and become a driving force behind the transformation of Southeast Asia’s most innovative enterprises. In this strategic role, you’ll embed directly with our high-impact customers in Bali and across the region, accelerating their adoption of Google Cloud’s cutting-edge AI and machine learning solutions. This is your chance to shape the future of AI-driven business while working in one of the world’s most dynamic tech hubs—Bali, where innovation meets tropical inspiration.

As a trusted advisor, you’ll collaborate with C-level executives, data scientists, and engineering teams to design, implement, and scale AI solutions that solve real-world challenges. From generative AI to predictive analytics, you’ll leverage Google’s unparalleled infrastructure to help customers unlock new revenue streams, optimize operations, and redefine customer experiences. This role blends deep technical expertise with business acumen, offering a unique opportunity to influence how enterprises harness AI for competitive advantage.

At Google, we’re committed to building a diverse and inclusive workplace. We encourage applications from professionals with a passion for AI, cloud technologies, and driving measurable impact. If you thrive in fast-paced environments, enjoy solving complex problems, and want to work with the brightest minds in tech—this is your moment.

Responsibility

  • Partner with enterprise customers in Bali and Southeast Asia to identify AI/ML use cases and drive adoption of Google Cloud’s AI portfolio, including Vertex AI, Generative AI, and AutoML.
  • Design and implement scalable AI solutions tailored to customer needs, ensuring alignment with business objectives and technical feasibility.
  • Collaborate with cross-functional teams (sales, product, engineering) to deliver proof-of-concepts (POCs) and pilot programs that demonstrate the value of Google Cloud AI.
  • Provide technical leadership and best practices for AI/ML model development, deployment, and monitoring, including MLOps and responsible AI frameworks.
  • Educate customers on Google Cloud’s AI capabilities through workshops, demos, and technical deep dives, positioning yourself as a trusted advisor.
  • Gather customer feedback to influence Google Cloud’s AI product roadmap and improve solution offerings.
  • Stay ahead of industry trends in AI/ML, cloud computing, and emerging technologies to provide forward-thinking guidance to customers.
  • Travel occasionally to customer sites (regionally) and represent Google at industry events, conferences, and meetups.

Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
  • 5+ years of experience in AI/ML, cloud computing, or enterprise software, with a focus on customer-facing roles (e.g., Solutions Architect, Customer Engineer, or Data Scientist).
  • Hands-on experience with Google Cloud Platform (GCP) or other major cloud providers (AWS, Azure), including AI/ML services like Vertex AI, TensorFlow, or BigQuery ML.
  • Proficiency in programming languages such as Python, Java, or Go, and familiarity with AI/ML frameworks (e.g., PyTorch, scikit-learn).
  • Strong understanding of MLOps, data pipelines, and cloud-native architectures (Kubernetes, Docker, serverless).
  • Excellent communication and presentation skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
  • Experience working with enterprise customers in Southeast Asia or emerging markets is a plus.
  • Passion for AI innovation and a track record of driving measurable business outcomes through technology.

Required Skills

AI/ML Google Cloud Platform (GCP) Vertex AI Generative AI TensorFlow Python MLOps Kubernetes Cloud Architecture Customer Engineering Stakeholder Management Technical Leadership Data Science Predictive Analytics

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