Talend Engineer (Big Data)

Lead Data Engineer

Ho Chi Minh, Ha Noi - Viet Nam

Outsource

Architect, develop, and maintain scalable data infrastructure, including data lakes, pipelines, and metadata repositories, ensuring the timely and accurate delivery of data to stakeholders. Work closely with data scientists to build and support data models, integrate data sources, and support machine learning workflows and experimentation environments. Develop and optimize large-scale, batch, and real-time data processing systems to enhance operational efficiency and meet business objectives. Leverage Python, Apache Airflow, and AWS services to automate data workflows and processes, ensuring efficient scheduling and monitoring. Utilize AWS services such as S3, Glue, EC2, and Lambda to manage data storage and compute resources, ensuring high performance, scalability, and cost-efficiency. Implement robust testing and validation procedures to ensure the reliability, accuracy, and security of data processing workflows. Stay informed of industry best practices and emerging technologies in both data engineering and data science to propose optimizations and innovative solutions.

Negotiation

Windows Engineer (C++/C#) - GSaaS

Ho Chi Minh - Viet Nam

Product

• C/C++

Develop and maintain applications using C# (WinUI framework) and C++ (Qt framework and Win32 API). Participate in the company's software development projects and collaborate with cross-functional teams on software architecture. Develop new features according to requirements, provide development documentation, and participate in code reviews. Troubleshoot, debug, and optimize performance for existing software features and applications. Write high-quality, testable code, ensuring adherence to high code quality standards. Research and integrate new technologies to enhance software products. Mentor junior developers and contribute to team knowledge sharing.

Negotiation

Senior AI Engineer

Ho Chi Minh - Viet Nam

Product

• Python
• AI
• Machine Learning

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

Negotiation