AI Outcome Customer Engineer, Google Cloud (Thai) - Singapore

GOOGLE ASIA PACIFIC PTE. LTD.

Singapore

On-site

SGD 120,000 - 180,000

Full time

5 days ago
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Job summary

Google Asia Pacific Pte. Ltd. seeks an AI Outcome Customer Engineer to bridge pre-sales and post-sales delivery for strategic AI accounts. You will architect integration of models, connectors, and data pipelines within customer IT ecosystems, coordinating with product and engineering teams.

You will lead technical evaluations, design enterprise-grade solutions, and diagnose complex deployment issues while aligning with regional client needs and compliance constraints.

Qualifications

  • Bachelor's degree or equivalent practical experience.
  • 7 years of experience with cloud native architecture in a customer-facing or support role.
  • Experience with technical delivery strategies and interfacing with product or engineering organizations.
  • Experience with enterprise integrations (APIs, ECMs, identity), cloud infrastructure, or AI/ML model deployments.
  • Experience reading or debugging code in a general purpose coding language (e.g., Java, Python, JavaScript), and in system design or orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI).
  • Ability to communicate in Thai fluently, to support client relationship management in this region.

Responsibilities

  • Partner with Account teams and Customer Engineer (CEs) during technical evaluation phases to assess project feasibility, shape proposals for long-term adoption, and validate FDE engagement requests.
  • Lead upfront technical design for enterprise-grade AI solutions, ensuring seamless and secure integration of models, agents, and connectors into existing customer data pipelines, identity providers, and compliance boundaries.
  • Dive into code-level context to diagnose and resolve complex customer implementation issues, identify core product bugs, and test workarounds to clear execution roadblocks.
  • Serve as the definitive liaison to core Product and Engineering teams, troubleshooting systemic deployment blockers and translating real-world field feedback into actionable feature requests.
  • Steer implementation strategy through technical authority and architectural foresight while owning the technical reality of delivery alongside customer-facing teams.

Skills

Cloud native architecture
Customer-facing delivery
Technical delivery strategies
Enterprise integrations
APIs
Identity management
Cloud infrastructure
AI/ML model deployment
Code debugging
Java, Python, JavaScript
Thai language fluency

Education

Bachelor's degree or equivalent practical experience

Tools

LangGraph
AutoGen
CrewAI

Job description

Product area

It's an exciting time to join Google Cloud's Go-To-Market team, leading the AI revolution for businesses worldwide. You'll excel by leveraging Google's brand credibility-a legacy built on inventing foundational technologies and proven at scale. We'll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We're a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era-the market is yours.

Job description

As an AI Outcome Customer Engineer, you work as an enterprise architect, technical debugger, engineering liaison and technical delivery manager. You will bridge the gap between pre-sales agreement shaping and post-sales execution. Entering the agreement cycle during the technical evaluation phase for strategic AI accounts, you will ensure that solutions are shaped strictly through the lens of adoption, rapid activation, and viable delivery. Aligned with our Forward Deployed Engineering (FDE) organization, you will architect how these technical assets actually integrate into the customer's IT ecosystem (connectors, identity, data residency, legal constraints).

Qualifications
Job responsibilities
  • Partner with Account teams and Customer Engineer (CEs) during technical evaluation phases to assess project feasibility, shape proposals for long-term adoption, and validate FDE engagement requests.
  • Lead upfront technical design for enterprise-grade AI solutions, ensuring seamless and secure integration of models, agents, and connectors into existing customer data pipelines, identity providers, and compliance boundaries.
  • Dive into code-level context to diagnose and resolve complex customer implementation issues, identify core product bugs, and test workarounds to clear execution roadblocks.
  • Serve as the definitive liaison to core Product and Engineering teams, troubleshooting systemic deployment blockers and translating real-world field feedback into actionable feature requests.
  • Steer implementation strategy through technical authority and architectural foresight while owning the technical reality of delivery alongside customer-facing teams.
Minimum qualifications
  • Bachelor's degree or equivalent practical experience.
  • 7 years of experience with cloud native architecture in a customer-facing or support role.
  • Experience with technical delivery strategies and interfacing with product or engineering organizations.
  • Experience with enterprise integrations (APIs, enterprise content management (ECMs), identity), cloud infrastructure, or AI/ML model deployments.
  • Experience reading or debugging code in a general purpose coding language (e.g., Java, Python, JavaScript), and in system design or orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI).
  • Ability to communicate in Thai fluently, to support client relationship management in this region.
Preferred qualifications
  • Experience diving deep into novel technical problems, deciphering ambiguity, diagnosing bugs, and emerging with credible architectural solutions.
  • Experience orchestrating specialized technical resources to execute complex builds.
  • Experience engaging with, presenting to, and influencing technical stakeholders or executive leaders.
  • Excellent executive communication skills, capable of translating deep technical integration issues into business impact.
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