Ho Chi Minh City, Vietnam

Hi, I'm Leon Pham

Software Engineer

Software engineer building scalable backends and polished frontends. I work across the full stack — from APIs to UIs.

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AWS SA Certified2+ yrs exp

Experience

Mar 2025 — Present

Software Engineer

Now

Oven

Project: Monitoring Platform · Tackman

Built a centralized monitoring pipeline for internal projects using Grafana, Alloy, Loki, and Prometheus, making it easier for teams to track metrics, logs, and slow APIs
Designed and implemented a video upload and processing workflow that converts videos to HLS format (m3u8) using AWS MediaConvert and automatically generates subtitles, enabling the system to reliably handle 30+ concurrent video uploads without data loss
Optimized the subtitle-to-audio conversion pipeline on AWS Lambda, reducing processing time by 50% and resolving timeout issues for long subtitle files (30–60 minutes)
Built an automated pipeline for generating video assets, including multi-language subtitles and corresponding audio tracks, reducing manual work and improving content production efficiency

redis

node

postgresql

prisma

docker

typescript

react

aws

May 2024 — Feb 2025

Fresher Backend Developer

ATOM SOLUTION

Project: Digistore BVBANK · Apache Fineract

Implemented service separation to reduce system complexity, improving startup time and optimizing server resource utilization
Implemented data synchronization between databases using Debezium and Kafka, enabling near real-time data consistency across services and reducing reliance on manual data syncing or batch jobs
Researched and integrated Keycloak for single sign-on (SSO), centralizing authentication across multiple services, reducing duplicated auth logic, and improving both security and user experience

redis

python

postgresql

docker

Open Source

Personal research and open source projects I build outside of work.

longtk26 / ai-chatbot

Research on methodologies to extend AI model capabilities — tool function calling, Model Context Protocol (MCP), and Retrieval-Augmented Generation (RAG).

GitHub

Implemented tool function-calling with OpenAI API to enable AI agents to invoke external services dynamically
Integrated Model Context Protocol (MCP) via Google Calendar MCP to connect LLMs with real-world data
Built a RAG pipeline with LangChain, pgvector, and OpenAI embeddings to ground responses in private data
Developed a multi-turn chatbot UI with Gradio to demonstrate tool-augmented LLM interactions

PythonOpenAILangChainRAGMCPpgvector