Experienced AI Engineer with over 7 years of building and deploying scalable AI-driven products across Natural Language Processing, Conversational AI, and Large Language Models (LLMs). Hands-on expertise with Deep Learning frameworks (PyTorch, TensorFlow), LLM orchestration tools (LangChain, LlamaIndex), and cloud-based MLOps pipelines. Passionate about converting complex AI research into production-grade systems that deliver measurable business outcomes. Comfortable working in fast-paced environments with cross-functional teams.

• Languages: Python, JavaScript, Bash

• Frameworks: PyTorch, TensorFlow, Keras, Scikit-learn

• LLM & NLP: OpenAI, LangChain, Hugging Face, RAG, Transformers

• Tools & Platforms: Docker, Kubernetes, MLflow, Weights & Biases

• Cloud: AWS (SageMaker, Lambda), GCP (Vertex AI), Azure

• Databases: PostgreSQL, MongoDB, Redis, Pinecone, Qdrant

• MLOps: FastAPI, GitHub Actions, Airflow, Prometheus, Grafana

Conversational Commerce Platform - Hongkong

AI Developer, Jan 2023 – Present

Project description

• Built an enterprise-grade multi-tenant chatbot platform that powers personalized shopping conversations across retail websites using OpenAI's GPT-4 APIs.

Responsibilities 

• Designed and built a modular chatbot framework using LangChain and GPT-4, allowing scalable deployment across multiple clients with different intents and personalities.

• Integrated a RAG system with vector search (Pinecone) to enrich chatbot responses with up-to-date product and inventory information.

• Developed a tool-usage orchestration layer enabling the LLM to query APIs like order tracking, recommendations, and cart actions.

• Conducted extensive A/B testing and prompt optimization to reduce hallucination rate and improve CSAT scores.

• Collaborated closely with product teams to iterate on conversational UX and business use cases (e.g., upsell, retargeting).

• Implemented observability pipelines with Prometheus/Grafana to monitor latency, error rate, and fallback performance.

Technologies 

•  Python, OpenAI API, LangChain, FastAPI, Pinecone, AWS.

Healthcare Virtual Assistant - US

AI Developer, March 2022 – Aug 2024

Project description 

• Developed an AI assistant to help chronic disease patients track medication, book appointments, and understand symptoms using domain-tuned LLMs.

Responsibilities 

• Fine-tuned and evaluated domain-specific LLMs (BioBERT, MedPalm) to answer patient queries with clinical-level accuracy.

• Designed multi-turn dialog management logic to ensure conversation continuity while managing edge cases like unclear symptoms or conflicting medication.

• Integrated OpenAI Function Calling with Azure-hosted services for medication reminders, appointment scheduling, and doctor Q&A.

• Built a feedback learning loop to retrain the assistant based on real-world interaction logs, improving accuracy over time.

• Ensured HIPAA compliance by implementing strict data handling, masking, and logging policies in coordination with DevSecOps

Technologies 

• Python, Pytorch, Triton, AWS, Fast API, Flask, PostgreSQL, Docker, Kubernetes, Redis. 

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ML Platform for Smart Recruiting - US

AI Developer, Jan 2021 – Jun 2021

Project description 

• Created intelligent recommendation engines for a recruiting startup, matching candidates with jobs based on skill semantics.

Responsibilities

• Built and deployed a semantic matching engine between resumes and job descriptions using cosine similarity and FastText embeddings.

• Created an automated skill extraction tool using SpaCy + RegEx with feedback loops from recruiters to improve precision.

• Trained ranking models using XGBoost and LightGBM, optimizing for click-through rate and job acceptance probability.

• Developed a web-based internal analytics dashboard to visualize matching insights and user drop-off trends.

• Collaborated with frontend engineers to implement an interactive job suggestion assistant for candidates.

Technologies

• Python, Git, Transformers, BERT, Flask

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AI Chatbot for Banking Support - Vietnam

AI Developer, May 2018 – Oct 2020

Project description 

• Developed and deployed a Vietnamese-English bilingual chatbot for one of the top digital banks in Southeast Asia.

Responsibilities

• Engineered an intent classification and entity extraction system using a fine-tuned BERT model for 90+ banking use cases.

• Integrated chatbot with backend APIs to automate tasks such as balance inquiry, loan eligibility, and transaction alerts.

• Created a fallback mechanism for ambiguous inputs, using decision trees and heuristics to recover gracefully from failed intents.

• Localized the bot for Vietnamese language using VN-BERT and rule-based sentence normalization for dialect support.

• Deployed and maintained the solution in production using a microservices-based architecture on Kubernetes. 

Technologies

• Python, BERT, Rasa, Docker, Kubernetes, Firebase

VNU-HCM, University of Information Technology Ho Chi Minh City, Vietnam  

• Master of Science in Computer Science 2022 – 2024

• Bachelor of Science in Computer Science