AI Technical Enablement Lead, Forward Deployed Engineering

AI Chopping Block, Inc.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Google Cloud JAPAC is hiring an AI Technical Enablement Lead to design, execute, and scale a high-touch onboarding program for FDEs across the region. You will ensure new hires gain deep product expertise and mastery of customer engagement methodologies, while updating the curriculum in real time.

You will crowdsource SMEs across JAPAC and beyond to build a sustainable framework that elevates field readiness and drives long-term customer impact through structured AI training and hands-on

Qualifications

• Bachelor’s degree in Engineering, CS or equivalent practical experience.
• 5 years of experience with Python or similar languages.
• Experience deploying AI-driven solutions on cloud platforms (GCP).
• Experience building data pipelines with vector databases and RAG-like architectures.
• Experience leading technical discovery sessions.

Responsibilities

• Develop, execute and scale a high-touch technical onboarding program for FDEs across JAPAC.
• Coordinate SMEs across JAPAC/globally to enable field readiness.
• Design AI product deep technical training and materials for priority initiatives.
• Collaborate with technical sales to advise on enablement needs.

Skills

Python

AI

Data pipelines

Vector databases

RAG architectures

Technical leadership

Curriculum design

Education

Bachelor’s degree in Engineering or Computer Science

Equivalent practical experience

Tools

LangGraph

CrewAI

ADK

Job description

As part of the Google Cloud JAPAC AI Tech GTM team, the AI Technical Enablement Lead will be responsible for designing, executing, and scaling a comprehensive, high-touch technical onboarding program tailored specifically for FDEs across the region. Your role will act as the operational programmatic anchor for new talent, ensuring hires develop deep product expertise, master customer engagement methodologies, and complete rigorous skill-based capstones, because AI technologies and product interfaces iterate at speed, the lead will actively update the learning curriculum in real-time to keep the FDEs lock step with the nuanced needs of the JAPAC customer. Additionally, you will crowdsource and coordinate subject matter experts across JAPAC/globally, ultimately building a sustainable framework that elevates field readiness and drives long-term customer impact.

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.

• Develop deep technical enablement programs based off of Forward Deployed Engineer and Cloud AI CE requirements for learning of AI products.
• Map persona-based views of technical GTM field enablement needs, leading the development of curriculum for in-person, e-learning and other assets.
• Design, build and execute structured AI product deep technical training and enablement programs, and build-out of materials for P0, P1 and other priority AI initiatives.
• Integrate into technical sales teams to understand enablement needs and become a trusted advisor to technical AI leadership.

Minimum qualifications:

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 5 years of experience with software development using Python or similar coding languages.
• Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., GCP).
• Experience building pipelines for structured and unstructured data using both vector databases and Retrieval-Augmented Generation (RAG)-like architectures to power enterprise AI solutions.
• Experience leading technical discovery sessions.

Preferred qualifications:

• Master’s degree or PhD in AI, Computer Science, or a related technical field.
• Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
• Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.