AI/ML Engineer - 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 actually depend on for live decisions.We’re looking for an AI Engineer who builds production AI systems — not prototypes. What you ship here advises real investment decisions and runs on live financial data. Correctness, reliability, and the ability to know when a model is wrong are not optional.What you’ll do•    Design and build the multi-agent orchestration system: intent classification, tool routing, sub-agent coordination, and response synthesis across complex financial queries•    Implement and maintain the memory architecture: user profile memory, session context, and long-term behavioral memory across conversations•    Build and maintain the tool library that agents call: portfolio analyzer, market data fetcher, strategy backtester, scenario modeler, screener, report generator, and compliance checker•    Design multi-tier LLM routing: optimize for quality, latency, and cost simultaneously across different model tiers•    Build RAG pipelines: embedding financial documents, vector search, and context retrieval for grounded, source-cited responses•    Integrate quantitative signals from the research team into agent reasoning — alpha factors, regime indicators, portfolio optimization outputs•    Build LLM evaluation frameworks: golden-set regression tests, hallucination detection, factual accuracy scoring against verified financial data•    Build the observability stack for AI systems: token usage, latency per model tier, cost per conversation, and audit logs for complianceRequirements•    2+ years building production AI or LLM-powered systems — shipped to real users, not research projects•    Deep familiarity with LLM APIs in production: Claude, OpenAI, or Gemini — streaming, tool use, structured outputs, context window management•    Agentic framework experience: LangChain, LangGraph, or equivalent — you know when to use them and when to build your own•    RAG pipeline experience: embedding models, vector databases, retrieval quality evaluation•    Strong Python — async programming, clean architecture, testable code•    Production mindset: you instrument everything, handle failures gracefully, and know when the model is wrong before users doBonus points•    Experience in fintech or financial services AI: compliance constraints, explainability requirements, data sensitivity•    Knowledge of Vietnamese financial products: mutual funds, VN30F derivatives, equities, bonds•    Multi-agent system design: agent handoffs, tool orchestration, parallel sub-agent execution•    LLM evaluation and red-teaming for factual accuracy in high-stakes domains•    Familiarity with financial data sources: market data feeds, fund NAV series, macro indicators•    Prior experience with goal-based financial planning or robo-advisory systemsBenefits•    Competitive salary + performance bonus•    Full ownership of AI architecture decisions — you define how the agents think•    Direct collaboration with PhD-level quant researchers and institutional finance professionals on live systems•    Work on AI systems where domain depth is the moat — not just prompt engineering•    Clear growth path to Lead AI Engineer or AI Architect as XNO scales across SEA