.NET Software Engineer

Senior AI Engineer

Ho Chi Minh - Viet Nam

Product

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

Frontend Software Engineer (Middle/Senior/Lead)

Ho Chi Minh - Viet Nam

Product

• ReactJS
• Frontend

Front-end research and development of products, including designing, implementing, and optimizing user interfaces. Making technical decisions, reviewing code, and promoting best practices in development and architecture. Using relevant tools and platforms to address user experience challenges, integrate complex business logic, and deliver business solutions efficiently. Collaborating with stakeholders to analyze business needs, define technical requirements, and contribute to system architecture design and development. Researching emerging technologies and evaluating leading industry products to drive continuous improvement in user experience and overall product quality. Providing mentorship and guidance to junior developers and fostering a collaborative and knowledge-sharing environment. Leading big projects from end-to-end and mentoring/guiding team members.

Negotiation

AI Solution Engineer

Ho Chi Minh, Ha Noi - Viet Nam

Product

• Python
• AI
• Machine Learning

Designing AI Solutions: Development of AI Agents and RAG pipelines to automate intricate workflows in construction project management. Prompt Engineering & Optimization: Create, assess, and refine prompt-chaining strategies using frameworks such as LangChain and LangGraph. System Integration: Oversee the integration of AI capabilities into existing microservices, ensuring scalability and low latency. Cost & Performance Monitoring: Implementation of LLMOps to monitor token usage, model performance, and data security/privacy aspects (especially concerning sensitive data). Innovation: Stay abreast of the latest AI research and technologies, and propose enhancements to existing systems and workflows.

Negotiation