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Applied AI Engineer | LLM Systems for Real-World Workflows | Creator of AppliedAIApps | Data & AI | Ex-KPMG, Micron
I work at the intersection of data engineering, AI, and real-world business workflows — focusing on how to make AI systems actually usable in practice, not just theoretically powerful. Over the past several years, I’ve built and delivered data and analytics solutions across domains, with experience spanning data engineering, machine learning, and enterprise analytics (Ex-KPMG, Micron, NUS). Currently exploring LLM-driven approaches for structured data extraction and enterprise analytics workflows, with a focus on real-world applicability and system design. More recently, I’ve been focused on applied AI systems — particularly leveraging LLMs to solve operational problems involving unstructured data. One such initiative is OrderFlowAI, a system I built to automate order processing workflows that typically rely on unstructured email inputs. The solution extracts key information, converts it into structured formats, and incorporates a human-in-the-loop validation layer to handle real-world ambiguity and edge cases. This work reflects a broader interest of mine: Bridging the gap between AI capability and practical implementation in enterprise environments. I am currently exploring LLM-driven approaches for structured data extraction, workflow automation, and decision systems — with a focus on scalability, reliability, and real-world constraints. I’m particularly interested in opportunities (industry or research) where AI systems are applied to solve meaningful operational or analytical challenges. Always open to thoughtful discussions around applied AI, data systems, and LLM-driven architectures.
National University of Singapore
Masters degree, Knowledge Engineering
January 1, 2016 – January 1, 2017
Rajiv Gandhi Prodyogiki Vishwavidyalaya
Bachelor of Engineering (B.E.), Electrical, Electronics and Communications Engineering 76.75/100
January 1, 2008 – January 1, 2012
AppliedAIApps.com
Applied AI Builder – AppliedAIApps
January 1, 2026 – Present
Lidl & Kaufland Asia
Senior Engineering Manager Lead
February 1, 2025 – May 1, 2025
Singapore · Hybrid
KPMG Singapore
Data Science Manager
March 1, 2024 – February 1, 2025
Singapore · Hybrid
Micron Technology
Sr. Data Science Engineer
November 1, 2022 – February 1, 2024
Singapore · Hybrid
Micron Technology
Data Science Engineer
July 1, 2020 – October 1, 2022
Singapore · Hybrid
DSTA
Machine Learning Engineer
July 1, 2019 – July 1, 2020
i.am+
Machine Learning Engineer
July 1, 2017 – June 1, 2019
A*STAR - Agency for Science, Technology and Research
Data Scientist Intern
August 1, 2016 – March 1, 2017
Singapore
Tata Consultancy Services
System Engineer
November 1, 2012 – December 1, 2015
Pune Area, India
OrderFlowAI – AI-powered Order Processing Automation
January 1, 2026 – Present
Built an MVP to convert unstructured order emails into structured JSON outputs. Includes human-in-the-loop validation and batch processing support. Designed for real-world workflows and on-prem deployment. Try here :- https://orderflowai.vercel.app/
Cashflow Dashboard
May 1, 2025 – May 1, 2025
Skills: Tableau · Data Analytics · Data Analysis
CSV SQL Query Practice Tool
April 1, 2025 – April 1, 2025
A tool to practice the SQL by uploading the data in csv file. Handy tool to quickly analyze the data without any spinning of database server.
IntroBot - Introduce yourself with your own ChatGPT like chatbot
March 1, 2024 – March 1, 2024
IntroBot to introduce oneself. A ChatGPT like simple chatbot to answer on my behalf on questions related to me, my background, skills etc. #machinelearning #artificialintelligence #LLM #ChatGPT
Coffee Shop Sales Orders - Dashboard
February 1, 2024 – February 1, 2024
A Tableau dashboard showing monthly sales order of a coffee shop
DataGPT - Ask your data
September 1, 2023 – September 1, 2023
A open platform for anyone to upload their excel file data and ask any analytical question and get instant answers on their data. #streamlit #dataanalytics #dataapps
Text Mining on construction site accident reports
August 1, 2016 – December 1, 2016
Text Analytics project: Construction site textual data analytics In this project textual data on various accidents happened on a construction site was given and the goal of the project is do various finding from textual data like major cause of accidents etc. This project is to get practical hands on practice on various text mining methods and tasks. It helped in understanding various text analytics tasks and use of CRISP-DM in textual data. In this project concepts related to natural language processing were also used. This project was done using python2.7 as tool to perform various text mining tasks. This project gave the understanding of various steps involved in a text mining project and use of python to perform those tasks.
Data Warehouse & Business Intelligence
July 1, 2016 – December 1, 2016
Data Warehouse: An academic project on the data warehouse is been done as a part of coursework. This project helped to understand the basic concepts of data cubes, data modelling, dimensional modelling and various type of schema like star schema and snow flake schema.
Data Driven Dashboard using Tableau
July 1, 2016 – December 1, 2016
Visualization & Business Intelligence Project: A visualization is created using the tableau in this project and data used for visualization is the real estate property data scrapped from the web and data provided as a part of this academic project. The main aim of this project is to find the some new and valuable insight through visualization from the available data. This visualization can then further help to make critical business decision. The findings and visualization created as part of this project is presented and reviewed by the Vizili Singapore.
Intelligent System
July 1, 2016 – December 1, 2016
Hybrid Intelligence System: A hybrid system is created as a part of this project, this system is made by using fuzzy logic and predictive model to solve the business problem associated with campaign management for a bank. The fuzzy rules were extracted from the data provided and predictive model is also created on different set of labelled data provided.
Automatic PUB meter reading.
March 1, 2016 – June 1, 2016
Internet of Things : Automatic PUB meter reader In this project a prototype for capturing the meter reading and send it to server to save in database is done using python. Raspberry pi is used to mount the edge devices and capture the reading. As an initial idea image processing-optical character recognition, is adopted to capture the reading.
Recipe Recommendation System.
March 1, 2016 – June 1, 2016
Case Base Recommendation System: A recipe recommender A recipe recommendation is developed using myCBR as case base tool for all taxonomy and similarity measures and JAVA is used for the front end to develop the whole application and writing all business logic code. The recipe data is collected online from various sites.
Coffee Recommendation System
January 1, 2016 – April 1, 2016
Rule Base System: An Expert System Coffee recommendation system “Xperto” is built using CLIPS, this system gives you the option on which type of coffee a person must try depending upon the various inputs given by the customer while using the system. This project is developed for the client “Sensuri Coffee Company”.
Customer Prediction Model
January 1, 2016 – April 1, 2016
Data Analytics and Mining In this project, a classification model was built on the given customer dataset using R programming language, R studio as development environment and rattle data mining library in R as the data mining GUI tool. CRISP-DM methods were applied to the dataset for data cleaning, data preparation and data modeling. This classification model helps in predicting the potential customer which can buy new product. This project gave the understanding on data mining process and various machine learning algorithms. This project gave exposure to use of various machine learning techniques and concept related to neural net, svm and decision tree etc.
AI-Powered Supply Chains
Indian Institute of Management Mumbai
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse project portfolio, including academic, personal, and industry projects across various domains (e.g., finance, manufacturing, retail, AI startups). Their experience spans different company sizes and types (consulting, tech, government), suggesting adaptability. The target role of 'Data Analyst' might be a slight mismatch given their senior-level Data Science, ML, and Engineering Manager experience, which leans more towards advanced analytics, AI/ML development, and data platform leadership rather than pure data analysis. However, their foundational skills are highly relevant.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight leadership, collaboration with stakeholders, and mentoring junior team members, indicating strong soft skills. Their work on self-service analytics and data literacy initiatives suggests a proactive approach to operational efficiency and fostering a data-driven culture.