With over 7 years of professional engineering experience, including leading development teams within the financial sector to architect and build highly secure, enterprise-grade systems, I specialize in designing and deploying intelligent, autonomous Agentic AI systems.
While my roots are in complex data engineering, backend architecture, and automation, my focus is on building robust AI architectures that actively execute workflows, process live data, and solve real-world business problems. A successful AI agent requires an impeccable data pipeline and secure cloud infrastructure to function reliably; my background in high-stakes financial environments ensures your AI solutions are built on a rock-solid, production-ready foundation.
Why Work With Me? (My USPs)
* Enterprise-Grade Cloud & AI Infrastructure: As an AWS expert, I design highly secure, scalable cloud architectures (including landing zones and strict access controls) tailored for enterprise AI. I also utilize platforms like Vercel and Supabase to optimize running costs.
* Technical Versatility: Deep expertise in Python, Node.js, and Java, allowing me to build robust backend services, seamlessly integrate top-tier LLMs (OpenAI, Claude), and develop custom agentic workflows.
* Proven Leadership in High-Stakes Domains: Having led engineering teams in the financial sector, I bring rigorous software development standards, enterprise security compliance, and strategic planning to every AI project.
* Seamless Ecosystem Integration: I build agents that interact flawlessly with your existing infrastructure, from Google Workspace and REST APIs to custom enterprise databases and secure gateways.
Core Competencies
* Agentic AI & Conversational Systems: Developing specialized autonomous agents and voice-driven AI applications utilizing modern frameworks and advanced model orchestration.
* Enterprise AI Architecture: Designing scalable, secure AI systems utilizing advanced methodologies, including Reinforcement Learning from Human Feedback (RLHF), to align models with specific business logic.
* Backend & Cloud Engineering: Expert-level development in Python, Node.js, and Java, supported by comprehensive AWS infrastructure management and API development.
* Data Engineering for AI: Building the essential infrastructure for RAG (Retrieval-Augmented Generation). Proficient in constructing robust data pipelines, designing databases, and scraping large-scale datasets to power intelligent systems.
* AI-Powered Automation: Creating bespoke applications that automate complex, multi-step processes, such as intelligent scraping, alert dispatching, and dynamic text refinement.
PySpark
Machine Learning
Data Engineering
Python
Scrapy
SQL
Data Scraping
Amazon Web Services
MongoDB
Selenium
pandas
Databricks Platform
ETL Pipeline
Long N.
Ho Chi Minh City, Vietnam
$40/hr
4.4
92 jobs
๐ Top Rated Plus
ใ คใ คโ 9+ years of experience in Upwork
ใ คใ คโ Expert in Python, AWS Cloud, ReactJS, NodeJS
ใ คใ คโ Proven expertise in Web Scraping and Web Development
ใ คใ คโ Available 7 days/week
ใ คใ คโ Fluent English
ใ คใ คโ Certified AWS Solution Architect Associate
ใ คใ คโ Certified Agile Scrum Master
ใ คใ คโ Long-term project support
๐ข๐๐๐ผ๐ ๐ ๐พ๐ผ๐ ๐ฟ๐ ๐๐๐ ๐๐๐:
๐ธ Quickly build application prototype
๐ธ Create scalable web applications using microservice architecture (need website that can handle 100k+ users? I've got you!)
๐ธ Build minimum cost MVPs using serverless architecture (don't want to pay too much for MVP's infrastructure? We are here to help๐)
๐ธ Scrape websites regularly
๐ธ Provide long-term project support & maintenance
๐ธ Large scale distributed scraping projects
๐ข๐๐๐ ๐๐๐๐ฟ ๐๐, ๐๐:
๐ธ You have an idea but don't know how to turn it into a prototype
๐ธ You need to develop a prototype cheap and fast to test your ideas
๐ธ You need to maintain & develop a legacy web scraping / web application project
๐ธ You want your legacy web application to scale automatically
๐ธ You need to optimize for cost and speed for your web application / web scraper
๐ธ You need long-term support of data feeds / web maintenance
๐ธ High availability is important
๐ธ You want to customize an open-source project
๐ธ You want to build applications that can handle over 20M rows of data on a daily basis
๐ข๐๐๐๐ ๐ฝ๐๐๐๐๐๐๐ ๐๐ ๐๐๐๐๐๐๐ ๐๐๐๐ ๐๐:
๐ธ Iโve worked on 40+ web scraping / web development projects
๐ธ Iโve plenty AWS credits that can save you cost when developing a prototype
๐ธ I have a large code base of components that I can reuse to save your time and cost
๐ธ Commitment
๐ธ Relevant project-related suggestions
๐ธ Expert advice for best practices to optimize your software product
๐ท๏ธ๐ ๐ฌ ๐ง๐๐๐-๐ฆ๐ง๐๐๐๐ท๏ธ
Python, Scrapy, Puppeteer, PostgreSQL, MongoDB, DynamoDB, RedShift, Athena, AuroraDB, Selenium, BeautifulSoup, Requests, Proxy Rotation, ReactJS, NodeJS, NextJS, Django, Flask, AWS, Firebase, GCP, Docker, pySpark, ElasticSearch, Neptune, Neo4J
๐ธ๏ธ๐ฆ๐๐ ๐ฃ๐๐ ๐ช๐๐ ๐ฆ๐๐ฅ๐๐ฃ๐๐ก๐ ๐ฃ๐ฅ๐ข๐๐๐๐ง๐ฆ ๐ธ๏ธ
Developed a social network and freelance marketplace platform with integrated payment system
Developed a big data platform that updates data in real time and handles over 1M rows of data daily
Develop a stock analysis and optimization tool using Scipy and Python
Download and process over 25GB of trademark data and ingest into Elastic Search
Scrape 50 eCommerce websites for drop shippers
Scrape over 100 book sellers on Amazon daily for an eCommerce website
Scrape and compare over 1000 products daily on Amazon and eBay for price arbitrage
PySpark
TensorFlow
Python Scikit-Learn
Python
Machine Learning
Google Chrome Extension
Google Cloud Platform
React
Browser Extension
Docker
MySQL
Selenium WebDriver
Amazon Web Services
Tam L.
Ho Chi Minh City, Vietnam
$50/hr
4.5
13 jobs
Most AI projects donโt fail at the model. They fail because the data underneath is broken.
I architect both layers โ the data platform (medallion, lakehouse, streaming) and the AI on top (RAG, document intelligence, agents). One architect, one cohesive system. No gaps between data team and AI team.
Recent work:
โข Data platform proposal for a network equipment manufacturer โ medallion on Databricks, polyglot serving with Cosmos + Synapse
โข AI variance detection for a US PEO platform on Azure AI Foundry
โข Document intelligence on SharePoint for a Japanese logistics enterprise
Stack: Azure, Databricks, Fabric, Snowflake, Azure AI Foundry, Azure OpenAI, .NET 8, Python/PySpark, React.
If youโre shipping AI but the data layer keeps breaking, or rebuilding data and want it AI-ready โ letโs talk.
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