AI Engineer

A. Key Responsibilities
Identify and assess AI use cases based on business, technical, and governance requirements.
Design and implement AI/GenAI solutions, including chatbots, AI assistants, RAG systems, document search, summarization, and report generation.
Develop AI Agents, prompt engineering frameworks, and end-to-end RAG pipelines.
Build, deploy, and optimize ML, LLM, MLOps, and LLMOps solutions.
Integrate AI applications with enterprise platforms such as SAP, Microsoft 365, SharePoint, and internal systems.
Deploy and manage Microsoft Copilot, Azure OpenAI, Claude AI, and other enterprise AI platforms.
Ensure AI governance, security, compliance, and responsible AI practices in accordance with ISO, NIST, and applicable regulations.
Collaborate with business and IT stakeholders to drive AI adoption and digital transformation initiatives.
B.
Qualifications & Skills
Bachelor's degree in Computer Science, AI, Data Science, Software Engineering, or related fields.
3+ years of experience in AI, Machine Learning, Data Science, or Generative AI development.
Strong proficiency in Python and AI frameworks/libraries such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, and LlamaIndex.
Solid understanding of Machine Learning, Deep Learning, LLMs, RAG, AI Agents, and Prompt Engineering.
Experience with vector databases, Azure OpenAI, Microsoft Copilot, Azure AI Search, Pinecone, Weaviate, or similar technologies.
Familiarity with MLOps/LLMOps, SQL, cloud platforms (Azure/AWS/GCP), Docker, and Kubernetes.
Knowledge of AI Governance, Responsible AI, Information Security, and Data Privacy principles is preferred.
C.
Preferred
Certifications
Microsoft Azure AI Fundamentals (AI-900).
Azure AI / Azure OpenAI Applied Skills certifications.
AWS or Google Cloud AI/ML certifications.
Responsible AI or AI Governance certifications are an advantage.
D. Other information
Working location: Vung Tau (on-site)
Working time: Mon - Sat (7:30 - 17:00)