Senior AI Engineer

Develop and deploy AI/ML systems for banking applications on AWS with a focus on reliability, scalability, and performance.

Maintain MLOps pipelines using AWS services, including model versioning, monitoring, and automated retraining workflows.

Utilize AI solutions for various banking use cases, such as fraud detection, customer relationship mapping, and network analysis.

Troubleshoot production AI systems and resolve issues in model performance, data pipelines, and AWS infrastructure.

Implement automated monitoring, alerting, and incident response for AI systems on AWS and optimize model serving infrastructure.

Build and maintain 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 regulations and security standards in all AI deployments and monitor model performance in production.

Stay updated with the latest AI research and evaluate its 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.

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.

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.

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).

Banking and Finance: Experience in the banking or finance industry is a plus.

Company offers meal and parking benefits.

Full benefits and probationary salary provided.

Insurance coverage as per Vietnamese labor law and premium health care for employees and their families.

Work environment is values-driven, international, and agile in nature.

Opportunities for overseas travel related to training and work.

Participation in internal Hackathons and company events such as team building, coffee runs, and blue card activities.

Additional benefits include a 13th-month salary and performance bonuses.

Employees receive 15 days of annual leave and 3 days of sick leave per year.

Work-life balance with a 40-hour workweek from Monday to Friday.

PEGASI – IT Recruitment Consultancy | Email: recruit@pegasi.com.vn | Tel: +84 28 3622 8666