Senior Manager, Data & AI Engineer leading data & AI engineering capabilities for AI Transformation programs across projects in China. Collaborating with global teams to enhance data governance and product delivery.
About the role
- AI Engineer leveraging extensive AI research and engineering skills for scalable banking solutions. Focused mainly on deploying AI/ML systems and staying current with cutting-edge technologies.
Responsibilities
- AI Engineering & Deployment (80%)
- Design, build, and deploy production-ready AI/ML systems on AWS with focus on reliability, scalability, and performance for banking applications
- Implement and maintain MLOps pipelines using AWS services (SageMaker, Bedrock, Lambda, Step Functions) including model versioning, monitoring, and automated retraining workflows
- Build and optimize AI solutions using AWS Bedrock, OpenAI API, and Gemini API combining with Model Context Protocol (MCP), Agent-to-Agent (A2A) protocol for various banking use cases
- Design and implement prompt engineering frameworks and prompt management systems for LLM-based applications
- Develop graph analysis solutions for fraud detection, customer relationship mapping, and network analysis in banking contexts
- Debug and troubleshoot production AI systems, identifying and resolving issues in model performance, data pipelines, and AWS infrastructure
- Build and maintain AIOps practices including automated monitoring, alerting, and incident response for AI systems on AWS
- Optimize model serving infrastructure for latency, throughput, and cost-efficiency using AWS services
- Implement robust data pipelines using AWS Glue, Kinesis, and related services for training and inference
- Collaborate with software engineering and risk teams to integrate AI capabilities into banking products and services
- Ensure compliance with banking regulations and security standards in all AI deployments
- Monitor model performance in production and implement drift detection and retraining strategies
- AI Research & Innovation (20%)
- Stay current with latest AI research papers and breakthroughs, evaluating applicability to banking and financial services
- Research and prototype emerging AI architectures and techniques for financial use cases
- Evaluate new paradigms in model training, inference optimization, and architectural innovations
- Share knowledge through technical discussions, paper reviews, and internal research presentations
- Identify opportunities to apply cutting-edge research to improve fraud detection, customer service, risk assessment, and other banking operations
Requirements
- Master's or PhD in Computer Science, AI/ML, Mathematics, Statistics, or related field with focus on machine learning, deep learning, or strong publication record or demonstrated deep understanding of AI research (thesis, projects, or contributions to the field)
- Deep theoretical knowledge of modern AI architectures and training methodologies
- Deep understanding of transformer architectures and attention mechanisms
- Strong knowledge of large language models (LLMs), multimodal models, and their architectural evolution
- Familiarity with current research trends including Agentic AI systems
- Retrieval-augmented generation (RAG) for banking context integration
- Test-time compute scaling and inference optimization
- Multimodal learning (document understanding, vision-language models)
- Long-term and short
- Experience integrating and managing external AI APIs:
- OpenAI API (GPT models, embeddings, fine-tuning)
- Gemini API (Google's multimodal models)
- Expertise in prompt engineering, prompt management, and LLM-powered Agents orchestration frameworks
- Strong knowledge of graph databases and graph analysis techniques: AWS Neptune or similar graph databases
- Graph algorithms for fraud detection and network analysis
- Knowledge graph construction and reasoning
- 8+ years of experience
- Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow)
- Hands-on experience with MLOps tools (MLflow, Weights & Biases, Airflow)
- Experience with containerization and orchestration (Docker, ECS, EKS)
- Strong understanding of distributed training and GPU optimization on AWS
- Experience with CI/CD pipelines using AWS CodePipeline or similar
- Ability to debug complex distributed systems and data pipelines
- Strong software engineering principles and version control (Git)
- Experience in the banking or finance industry is a plus.
Benefits
- Performance bonus up to 2 months
- 13th month salary
- 15-day annual leave+ 3-day sick leave + 1 birthday leave + 1 Christmas leave
- Meal and parking allowance are covered by the company.
- Full benefits and salary rank during probation.
- Insurances as Vietnamese labor law and premium health care for you and your family
- SMART goals and clear career opportunities (technical seminar, conference, and career talk) - we focus on your development.
- Values-driven, international working environment, and agile culture.
- Overseas travel opportunities for training and working related.
- Internal Hackathons and company's events (team building, coffee run, blue card...)
- Work-life balance 40-hr per week from Mon to Fri.
Job title
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Tech skills
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