AI-Powered Procurement Intelligence Platform - Singapore
AI Engineer, Mar 2025 - Present
Project description
- Developed and maintained AI-powered solutions for a B2B procurement platform, enabling intelligent product discovery, categorization, semantic search, recommendations, and LLM-driven procurement assistants. Built scalable backend services and retrieval-based AI workflows to improve search relevance, product matching accuracy, and user experience across enterprise procurement operations
Responsibilities
- Designed and implemented AI-powered product intelligence solutions, including product categorization, semantic search, recommendation engines, and LLM-based assistants.
- Developed scalable backend services, REST APIs, and data processing pipelines supporting production-grade AI applications
- Built Retrieval-Augmented Generation (RAG) workflows integrating vector search, business-specific knowledge, and LLM capabilities to improve answer quality and retrieval accuracy.
- Implemented semantic search and embedding-based retrieval systems to enhance product discovery and procurement decision-making.
- Collaborated closely with product managers and engineering teams to transform business requirements into production-ready AI solutions.
- Developed and optimized AI service deployment pipelines using Docker and cloud platforms, improving scalability, reliability, and maintainability of AI services.
- Conducted code reviews, testing activities, and engineering best-practice initiatives to ensure high-quality production systems.
- Contributed to feature design, architecture discussions, and iterative enhancement of customer-facing AI products.
Technologies
- Python, Fast API, REST APIs, OpenAI API, LangChain, Lang Graph, Semantic Search, RAG, Hugging Face, Sentence Transformers, PostgreSQL, MySQL, Docker, GitHub Actions, CI/CD, Git, Cloud Platforms
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.
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
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
