AI Outcome Customer Engineer

Google LLC; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Google LLC in Singapore seeks an AI Outcome Customer Engineer to bridge pre-sales to delivery, architecting adoption-focused solutions and ensuring rapid activation within customer IT ecosystems. You will lead enterprise-grade AI integrations across connectors, identity, data residency and compliance, collaborating with GTM and engineering to deliver measurable business impact.

This role requires strong executive communication, deep technical fluency across cloud-native architectures, and the

Qualifications

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

Responsibilities

• Architect how AI assets integrate into the customer's IT ecosystem (connectors, identity, data residency, legal constraints).
• Bridge the gap between pre-sales agreement shaping and post-sales execution during technical evaluation phases.
• Lead upfront technical design for enterprise-grade AI solutions, ensuring secure and seamless integration.
• Collaborate with Account teams and Practice Customer Engineers during evaluation phases to assess feasibility and long-term adoption.
• Diagnose and resolve complex customer implementation issues and translate field feedback into feature requests.

Skills

Cloud native architecture

System design

Delivery strategies

Product/Engineering liaison

Code reading (Java, Python, JS)

APIs/ECMs/identity integrations

Education

Bachelor's degree or equivalent practical experience

Tools

LangGraph

AutoGen

CrewAI

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).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.

Minimum qualifications:

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

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.
• - Partner with Account teams and Practice 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.