XNO - Mid-level Engineer (AI) - HCM

XNO is a quantitative AI technology company building institutional-grade financial infrastructure for professional investors across Vietnam and Southeast Asia. We operate at the intersection of systematic trading, AI, and financial data, serving fund managers, trading desks, and wealth professionals with tools they depend on for live decisions.
We are looking for an AI Engineer to build and improve XNOBrain, our AI-powered financial intelligence platform. You'll work with LLMs, AI agents, and financial data to develop intelligent, reliable systems that support real investment workflows.
What you'll do
Design, develop, and improve AI-powered features using LLMs, RAG, and agent-based architectures.
Build and maintain AI agent workflows, including tool integration, task orchestration, and context management.
Develop RAG pipelines to retrieve and process financial documents, market data, and other relevant information.
Integrate AI models with backend services, internal APIs, and financial data systems.
Improve AI response quality, reliability, and performance through evaluation, testing, and optimization.
Develop scalable backend components to support AI applications in production.
Collaborate with Quant Researchers, Software Engineers, and Product teams to deliver AI solutions for financial analysis and investment workflows.
Requirements
Hands-on experience building and deploying AI/LLM-powered applications in real-world environments.
Strong Python programming skills and solid software engineering fundamentals.
Practical experience with LLM APIs, prompt engineering, tool calling, and structured outputs.
Experience with RAG, vector databases, and information retrieval techniques.
Familiarity with AI agent frameworks and multi-step agent workflows.
Experience developing backend APIs and integrating external services.
Understanding of LLM evaluation, testing, and techniques for improving response accuracy and reliability.
Familiarity with Docker, Git, and modern software development practices.
Strong problem-solving skills and ability to work independently on assigned features.
Bonus points
Experience with multi-agent systems, agent orchestration, or conversational AI.
Experience optimizing LLM performance, latency, and cost.
Familiarity with financial markets, investment research, or fintech applications.
Experience with financial data processing or data pipelines.
Familiarity with cloud infrastructure and production AI deployment.
Benefits
Competitive salary and performance bonus.
Opportunity to build production AI systems used in real financial and investment workflows.
Direct collaboration with experienced Quant Researchers and financial domain specialists.
Ownership of meaningful AI features and opportunities to contribute to technical decisions.