Hybrid Senior AI Engineer – Research

at qode.world

• Job title: Senior AI Engineer – Research
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: Airflow, AWS, Distributed Systems, Docker, Python, PyTorch, Tensorflow
• Location requirements: Hybrid, Ho Chi Minh, Vietnam

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.