(Senior) AI R&D Engineer (Bank, Agentic AI development, GCP & Google Gemini; Cantonese Speaking needed!!!)

JustOneGalaxy Recruitment; Hong Kong; On-site; HKD 900,000 - 1,400,000; Full time

Job summary

JustOneGalaxy Recruitment seeks an (Senior) AI R&D Engineer to research, design, develop, and deploy cutting-edge AI solutions for banking processes. You will work hands-on on R&D, leveraging GCP Vertex AI, Google Gemini, and Agentic AI to build intelligent systems and deploy them into production.

You will bridge AI model development, cloud integration, and application engineering, collaborating with cross-functional teams to deliver measurable business value while complying with regulatory

Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related quantitative field.

Responsibilities

• Lead the R&D and implementation of Agentic AI frameworks, multi-agent systems, and Generative AI applications.
• Design and deploy advanced AI solutions powered by Google Gemini and foundation models, fine-tuning them on banking-specific data for domain-critical tasks.
• Architect and manage AI solutions on Google Cloud Platform (GCP) such as Vertex AI, including model training, deployment, data pipelines, and hosting.
• Build interactive prototypes and user interfaces with Python frameworks (Streamlit, Flask, Gradio) and front-end tooling to demonstrate agentic AI capabilities.
• Connect AI models and agentic workflows to core banking systems via secure RESTful APIs, ensuring data flow, security, and performance.
• Develop MLOps and CI/CD pipelines on GCP to support monitoring, automated updates, and production deployment.
• Collaborate with product managers, data scientists, and business stakeholders to translate needs into technical execution while meeting regulatory standards.

Skills

Agentic AI development

GCP / Vertex AI

LLM tuning & fine-tuning

REST APIs

Python for AI engineering

MLOps & CI/CD

Cross-functional collaboration

Education

Bachelor’s or Master’s in CS/DS/AI

Tools

Vertex AI

Google Gemini

LoRA/QLoRA

PyTorch

TensorFlow

Streamlit/Flask/Gradio

Job description

The (Senior) AI R&D Engineer is responsible for researching, designing, developing, and deploying cutting-edge AI solutions to enhance business processes and solve complex challenges within the bank. This role focuses on hands-on Research & Development (R&D), leveraging Google Cloud Platform (GCP), Google Gemini, and Agentic AI development to build intelligent, high-impact systems.The ideal candidate bridges AI model development, cloud integration, and application engineering. Collaborating with cross-functional teams, you will build and fine-tune large language models (LLMs), architect agentic workflows, develop REST APIs, and integrate AI services into existing infrastructure. Strong communication skills are essential to align technical capabilities with business goals, ensuring innovative AI applications deliver measurable value across banking operations.Key ResponsibilitiesAgentic AI & Generative AI Development: Lead the R&D and implementation of Agentic AI frameworks, multi-agent systems, and Generative AI applications. Design and deploy advanced AI solutions powered by Google Gemini and leading foundation models, fine-tuning them on banking-specific data for domain-critical tasks such as compliance, risk control, and operational automation.

• GCP Ecosystem & Cloud Architecture: Architect and manage AI solutions natively on Google Cloud Platform (GCP) (e.g., Vertex AI), utilizing GCP services for model training, deployment, data pipelines, and application hosting.
• Machine Learning Model Lifecycle Management: Build, train, and optimize machine learning models with strong feature engineering and generalization mechanisms to maintain effectiveness across evolving banking use cases.
• Prompt & Harness Engineering: Apply advanced prompt engineering strategies (e.g., few-shot, chain-of-thought). Research and evaluate emerging harness engineering frameworks and tools (e.g., Hermes Agent, DeepSeek Harness, Claude Code) to drive automated development and intelligent operations.
• AI Prototyping & Application Development: Rapidly construct interactive prototypes and user interfaces using Python frameworks (e.g., Streamlit, Flask, Gradio) and front-end tooling to demonstrate agentic AI and Gen AI capabilities.
• System Integration & API Engineering: Connect AI models and agentic workflows to core banking systems and backend services via robust RESTful APIs, ensuring seamless data flow, security, and performance.
• MLOps & Pipeline Management: Build and maintain scalable MLOps and CI/CD pipelines on GCP to support real-time monitoring, automated updates, and seamless model deployment in production environments.
• Cross-Functional Collaboration & Innovation: Work alongside product managers, data scientists, and business stakeholders to translate strategic business needs into technical execution while adhering to regulatory and compliance standards.

Qualifications & Requirements

Education: Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related quantitative field.

• Core Technical Expertise:
• Strong hands-on experience in Agentic AI development (agent frameworks, tool-use, multi-agent orchestrations).
• Demonstrated proficiency with Google Cloud Platform (GCP), including Vertex AI and cloud-native AI deployment.
• Deep experience working with Google Gemini models and parameter-efficient fine-tuning (e.g., LoRA, QLoRA).
• Proven track record in AI R&D, model lifecycle management, and full-stack AI integration.
• Programming & Tools:
• Expert proficiency in Python for backend AI engineering, scripting, and rapid prototyping.
• Experience with standard frameworks (PyTorch, TensorFlow) and UI tools (Streamlit, Flask, Gradio).
• Prompt & System Design: In-depth knowledge of prompt engineering techniques (few-shot, reasoning chains) and exposure to autonomous agent workflows.
• APIs & Data: Strong capability in designing, building, and consuming RESTful APIs, with experience handling data integrations securely.
• Soft Skills: Outstanding problem-solving skills, agile mindset, and the ability to articulate complex AI concepts to cross-functional stakeholders within the bank.