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Google
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AI Solutions Engineer, GenAI Applications, Global Business Consulting
Singapore
· Full-time
·
Not Applicable
Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.Minimum qualifications:
In this role, you will have an opportunity to work closely with mobile games and apps developers, translating data into innovative AI-driven products that directly enable the growth of their businesses.
Responsibilities
- Bachelor's degree or equivalent practical experience.
- 3 years of experience troubleshooting technical issues for internal/external partners or customers.
- Experience in either system design or reading code (e.g., Java, C++, Python).
- 6 years of experience writing and maintaining ETL pipelines operating on a variety of structured and unstructured data sources.
- Experience applying Generative AI technologies to enterprise-scale products and solutions, within a quantitative domain. (Google Agent Development Kit (ADK), Lang-Chain etc. RAG).
- Understanding of MLOperations/LLMOperations practices for productionizing AI agents and models and Knowledge of cloud-native platforms (e.g., Google Cloud/GCP).
- Ability to break down ambiguous problems and propose solutions through data modeling and system design.
- Excellent communication skills to communicate technical concepts to non-technical stakeholders.
In this role, you will have an opportunity to work closely with mobile games and apps developers, translating data into innovative AI-driven products that directly enable the growth of their businesses.
Responsibilities
- Design, build and maintain secure data pipelines Extract, Transform, Load (ETL) required for GenAI and ML models, integrate and prepare various datasets for model training and serving.
- Implement components of full-stack Generative AI applications, focusing on data-centric techniques such as RAG and Fine-tuning.
- Develop and maintain Large Language Models (LLM)-based agents, including configuring RAG workflows and utilizing advanced prompt engineering techniques like Multi-hop Chain of Thought Prompting (MCP).
- Adhere to MLOps standard procedures for deploying, monitoring, and maintaining Generative AI models and data systems in production environments, ensuring performance and reliability.
- Collaborate with data scientists, consultants, and business stakeholders to implement production-ready solutions.
Key Skills
Ranked by relevance
ai
etl
cloud
mlops
java
c
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- Posted
- Jun 17, 2026
- Type
- Full-time
- Level
- Not Applicable
- Location
- Singapore
- Company
Industries
Information Services
Technology
Information
Internet
Categories
Project Management
Consulting
Engineering
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