Senior AI Engineer

JOB DESCRIPTION

We're seeking an AI Engineer with strong academic foundations and deep technical expertise who excels at translating research into production banking systems. This role is 80% focused on engineering excellence-deploying models, optimizing infrastructure, ensuring reliability, and solving real-world implementation challenges-and 20% on staying current with cutting-edge AI research and emerging technologies. You'll bridge the gap between state-of-the-art AI research and scalable production systems in the financial services sector.
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

JOB REQUIREMENT

Education & Research Background
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
Technical Expertise (AI Landscape)
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
Engineering Skills
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)
Additional Experience:
Banking and Finance: Experience in the banking or finance industry is a plus.

WHAT'S ON OFFER

Performance bonus up to 2 months
13th month salary pro-rata
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 without seniority compulsory
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.

CONTACT

PEGASI – IT Recruitment Consultancy | Email: recruit@pegasi.com.vn | Tel: +84 28 3622 8666
We are PEGASI – IT Recruitment Consultancy in Vietnam. If you are looking for new opportunity for your career path, kindly visit our website www.pegasi.com.vn for your reference. Thank you!

Job Summary

Company Type:

Product

Technical Skills:

Python, AI, Machine Learning

Location:

Ho Chi Minh - Viet Nam

Working Policy:

Hybrid

Salary:

Negotiation

Job ID:

J02043

Status:

Active

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