AI Engineer

About the role

Beyondsoft, a mid-sized business IT and consulting company with offices across four continents, is hiring an AI Engineer in Hanoi. The team is moving toward an AI-native decision-intelligence function, and the engineer will design and build intelligent experiences on top of a Data & Intelligence foundation: agentic workflows, natural-language queries, automation and programmatic access patterns. The role combines AI application development with enterprise data-governance awareness.

Key responsibilities

• Design AI-native ways to interact with data through natural language, agents, assistant-style interfaces and CLI access.
• Build prototypes and production workflows for KPI lookup, report health checks, quality validation, insight routing and stakeholder self-service.
• Partner with Data Engineers to base AI experiences on trusted semantic models and governed data assets.
• Work with Business Analysts to encode business context, metric interpretation, ontology and guardrails into AI experiences.
• Support AI-native skilling and engineering practices, including human-in-the-loop needs and capability gaps.
• Drive automation such as reporting, alert/response, validation and insight routing.
• Apply responsible AI, security, entitlement and governance principles throughout.
• Define reusable architecture patterns for AI-enabled decision intelligence.

Required profile

• At least 2 years of hands-on AI/GenAI project experience, with real project involvement beyond just listing tools.
• Experience building AI applications, agents, assistants or LLM-integrated workflows, able to explain what was built and the decisions made.
• Ability to debug and evaluate AI systems and judge cost, latency and reliability trade-offs.
• Comfortable working close to the metal, e.g. implementing tool-calling loops yourself.
• Solid software engineering foundation: system design, data structures, concurrency, error handling, and standard practices such as Git, CI/CD, testing, logging and monitoring.
• Occasional in-person activity may be required.

Required skills

• LLM applications, RAG, agents, prompt engineering, model integration, evaluation and production deployment.
• Microsoft stack (.NET/C#, Azure, Azure OpenAI, Microsoft Fabric).
• Data engineering is a plus: dimensional modeling, ETL pipelines and big data.
• Familiarity with enterprise data platforms and semantic layers.
• Programming in Python and/or TypeScript/C#.