AI Engineer

1. AI Agent & Chatbot Development  

• Design and implement AI-driven chatbots using LLMs (e.g., GPT, LLaMA, Mistral, etc.).  

• Build domain-specific pipelines to integrate organizational/public health knowledge into conversational agents.  

• Ensure chatbot responses are accurate, contextual, and aligned with public health values.  

2. Search & Personalization 

• Develop semantic search engines and retrieval-augmented generation (RAG) pipelines.  

• Implement personalization features (user profiling, adaptive responses).  

• Optimize relevance and ranking for search results using ML/AI techniques.  

3. Virtual Assistant Capabilities  

• Extend AI agents to support virtual assistant features: task reminders, workflow automation, and knowledge support.  

• Integrate with productivity tools (calendars, CRM, digital platforms).  

4. Technical Development & Integration  

• Fine-tune and deploy LLM models in secure and efficient environments.  

• Ensure scalability, performance optimization, and responsible use of AI.  

• Collaborate with cross-functional teams (Product Owner, developers, domain experts, QA).  

5. Data Engineering & Preparation  

• Collect, clean, and preprocess structured and unstructured datasets for model training.  

• Build and maintain pipelines for knowledge ingestion (documents, APIs, databases).  

• Ensure data quality, labeling consistency, and bias mitigation.  

6. Monitoring & Continuous Improvement  

• Monitor model performance post-deployment (latency, accuracy, hallucination rates, user adoption).  

• Implement feedback loops for continuous learning and model updates.  

• Detect and mitigate model drift or degraded performance.  
  

7. Security, Ethics & Compliance  

• Ensure compliance with data protection and ethical AI principles (privacy, fairness, transparency).  

• Implement safeguards to reduce risks of hallucinations, misinformation, and bias in chatbot outputs.  
  

8. Innovation & Documentation  

• Stay updated with AI/ML advancements, particularly in LLMs, agent frameworks, and healthcare AI.  

• Document development processes, model architectures, and APIs.  

• Contribute to knowledge-sharing sessions and training for internal teams.  

           QUALIFICATIONS, COMPETENCIES AND EXPERIENCE:

• Bachelor’s degree in Computer Science, AI/ML, Data Science, or related field (Master’s preferred).  

• Minimum 2 years of hands-on AI/ML experience, especially with LLM-based applications.  

• Proven track record in building chatbots, AI agents, or virtual assistants.  

• Strong coding skills in Python and frameworks (PyTorch, TensorFlow, LangChain, LlamaIndex).  

• Familiarity with MLOps, Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP).  

• Understanding of semantic search, personalization algorithms, and RAG pipelines.  

• Excellent problem-solving and analytical skills.  

• English and Vietnamese proficiency (French is an asset).  

• Experience in digital health or LMIC settings is highly desirable.  
  KEY DELIVERABLES:

• Functional AI chatbot integrated with domain knowledge.  

• Semantic search engine with RAG pipeline.  

• Personalization module tested with end-users.  

• Virtual assistant prototype (if feasible in project timeline).  

• Technical documentation (system design, APIs, models).  

• Reports on usage metrics, performance, and adoption.