Hello, I'm

Lakshay Dhawan

Forward Deployed Engineer @ tridorian

Building agentic AI systems on Google Cloud — Forward Deployed Engineer @ tridorian, turning solution designs into working systems. Computer Programming student, George Brown.

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Forward Deployed Engineer @ tridorian · since Aug 2026 · Toronto / GTA

About Me

Who I Am

I work as a Forward Deployed Engineer @ tridorian, deployed on Google Cloud engagements alongside Solutions Architects — turning solution designs into working systems. I also finish a Computer Programming & Analysis diploma at George Brown, and I came to software from a decade of hands-on work: moving logistics, a licensed electrician apprenticeship, retail tech. That background shows up in how I build: I care about the part of the system that exists in the messy real world.

These days I'm focused on Google Cloud and AI — building agentic AI systems: agent architectures, model routing, and evaluation loops. I hold both Google Cloud Professional certs — Cloud Architect and Machine Learning Engineer — and I pick up whatever the problem actually needs.

Career Statement

“I would rather have questions that can't be answered than answers that can't be questioned.” — Richard Feynman

I take that literally: I build things I have to answer for — RAG pipelines that actually retrieve, auth flows that survive merge conflicts, infra I can defend on a whiteboard.

5 Cloud Certifications
5 Projects & Capstone
2018 Working since
Credly badge: Google Cloud Certified Professional Machine Learning EngineerProfessional
ML EngineerCredly badge: Google Cloud Certified Professional Cloud ArchitectProfessional
Cloud ArchitectAzure Administrator
AZ-104 · 992722909Azure AI
AI-900 · 31305C-869C1AAzure Fundamentals
AZ-900 · I142-2996

Right Now

Focus

Google Cloud & AI — building agentic AI systems: agent architectures, model routing, and evaluation loops, mostly learned hands-on in customer environments.

Latest commits
  • Pulling from github.com/imlakshayd…
GitHub commit activity, last year

Resume

Lakshay Dhawan

Brampton, ON · Updated Oct 2026

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Summary

George Brown grad (Apr 2026) building full-stack systems with an ML lean. Most real engineering I’ve done was on Move-In, a 5-person capstone marketplace — I owned Supabase auth, migrations, Docker, and branch integration (top contributor, 24/51 commits). Outside that: a local RAG pipeline, two sklearn projects, and an Azure/GCP cert habit.

Skills

Languages

JavaScript C# Swift Java Python HTML CSS

Frontend

React.js React Router Material UI

Backend

Node.js Express.js REST APIs JWT bcrypt

Databases

MongoDB Mongoose ChromaDB

Tools / DevOps

Docker Docker Compose Git GitHub Postman

AI / ML

NumPy pandas matplotlib scikit-learn PyTorch Hugging Face Transformers LangChain Embeddings Vector Search RAG

Experience

Forward Deployed Engineer Aug 2026 – Present

tridorian • Toronto / GTA

  • Forward Deployed Engineer on Google Cloud customer engagements, working alongside Solutions Architects
  • Turning solution designs into working implementations on customer cloud environments
Technical Support & Repair Technician Jan 2026 – Present

GeekSquad (BestBuy) • Brampton, Ontario

  • Diagnose and resolve multifaceted hardware and software issues across laptops, desktops, and peripherals
  • Execute operating system deployments, secure data migrations, and system configurations
  • Manage a high-volume workload of 10–15 devices per shift, concurrently addressing multiple service requests
  • Utilize the Clarify Smarts ticketing system to track and manage service requests
  • Deliver clear technical support by translating intricate technical issues into simplified, actionable solutions
Computing Advisor Mar 2025 – Dec 2025

BestBuy • Brampton, Ontario

  • Assisted over 50 customers daily in locating merchandise, increasing customer satisfaction
  • Successfully up-sold additional warranty protection and store offers to 30% of customers
  • Averaged $1,500 in sales per hour through solution-based selling and specialized product expertise
  • Advised customers on laptops, networking, and peripherals, translating needs into optimized solutions
  • Consistently exceeded KPIs through strong communication and product knowledge
Chromebook Sales Specialist Oct 2024 – Feb 2025

Google (via Activation Services Inc.) • Brampton, Ontario

  • Generated over $250,000 in sales during the contract period
  • Achieved #1 national ranking for Chromebook sales across Canada during Q4
  • Delivered training sessions to Best Buy staff on Google product features and benefits
  • Engaged with customers to provide exceptional in-store experience and tailored recommendations
Front Desk Manager Jan 2024 – May 2024

Super 8 • Ajax, Ontario

  • Led and mentored a team of 10, increasing staff performance and guest satisfaction scores by 20%
  • Oversaw billing and financial transactions with a 98% accuracy rate
  • Boosted hotel revenue by 27% by promoting additional services and facilities
  • Managed room bookings and cancellations with 100% accuracy, reducing booking errors by 15%
Logistics Coordinator Dec 2021 – Dec 2022

Angus Consulting Management Limited • Vancouver, BC

  • Developed comprehensive daily work plans, achieving a 98% on-time completion rate
  • Streamlined inventory logistics, maintaining a 100% accuracy rate in tracking and organization
  • Led and mentored two junior movers, boosting team productivity
  • Collaborated with Building Operators and Journeyperson technicians
IT Intern (CO-OP) Sep 2018 – Sep 2019

Guru Tegh International School • Brampton, Ontario

  • Provided tier-I support and resolved tickets for 125+ onsite and remote end users
  • Responded to inquiries in-person or via email, chat, or telephone
  • Assisted in network troubleshooting, reducing system downtime by 15% over four months
  • Relocated users to new workstations, including moving and connecting assigned equipment

Education

Advanced Diploma – Computer Programming & Analysis 2026

George Brown College • Toronto, Ontario

Construction Maintenance Electrician 2024

Skilled Trades College of Canada • Mississauga, Ontario

Bachelor of Civil Engineering (Incomplete) 2020 – 2022

Queen's University • Kingston, Ontario

Certifications

Professional Machine Learning Engineer badge Google Cloud Certified: Professional Machine Learning Engineer 2026

Google • verify on Credly →

Professional Cloud Architect badge Google Cloud Certified: Professional Cloud Architect Aug 2026

Google • verify on Credly →

Azure Administrator Associate · AZ-104 Mar 2022

Microsoft · ID 992722909 • credential →

Azure AI Fundamentals · AI-900 Apr 2024

Microsoft · ID 31305C-869C1A • credential →

Azure Fundamentals · AZ-900 Feb 2022

Microsoft · ID I142-2996 • credential →

Machine Learning Coursework 2024

Kaggle — Intro to ML • Python • Pandas • Intro to Programming

First Aid & Safety Tickets

First Aid & CPR/AED Level C (Nov 2023–Nov 2026) • WHMIS 2015 • Lockout & Tagout • Working at Heights • REMIC Mortgage License — details on the downloadable resume

Community Service & Volunteer Work

Operations Executive — Volunteer Role Nov 2023 – May 2024

George Brown College • Huskies eSports Club (Unpaid, Extracurricular)

  • Managed team schedules, practices, and tournament participation, helping the club grow to over 1,500 members
  • Developed promotional strategies, increasing social media engagement by 30% and event attendance by 20%
  • Established and maintained robust relationships with critical sponsors, securing long-term deals
  • Ensured all activities adhere to college policies and esports regulations
Student Technician — Volunteer Role 2024

Enactus Canada • George Brown College Byte Club (Unpaid, Extracurricular)

  • Contributed to tech-focused initiatives within Byte Club under Enactus Canada
  • Collaborated with peers on project ideation, development, and execution
  • Supported planning and coordination of events promoting entrepreneurship and technology
  • Worked in a team-driven environment to build solutions with real-world impact

Awards & Recognition

Dean's List Winter 2026

George Brown College • Computer Programming & Analysis

#1 National Ranking — Chromebook Sales Q4 2024

Google (via Activation Services Inc.) • Canada-wide

Achieved top national ranking for Chromebook sales across all Canadian Best Buy locations during Q4, generating over $250,000 in revenue during the contract period.

Capstone Project

Move-In

A full-stack moving marketplace — a capstone proof of concept that validated the idea and never launched.

proof of concept · not launched
ReactNode.jsExpress.jsSupabaseJavaScriptCSS
View on GitHub →
Move-In app screen from the implementation evidence document
App build — implementation evidence
Move-In admin screen from the implementation evidence document
Admin dashboard
Figma mockup screen
Figma mockups

Project Summary

Move-In was a capstone proof of concept at George Brown College: a full-stack marketplace connecting customers who need moving services with movers offering their expertise. Built with React on the frontend and Node.js/Express on the backend, with Supabase for data and authentication. It was built to test whether the coordination model held up — it did, but the product never launched.

Project Vision

Explore whether one shared workspace — discovery, estimates, booking, progress tracking — could replace the phone-tag and text-thread coordination that real moves run on. As a proof of concept the question was answered; scaling it into a real marketplace was out of scope.

Business & Project Requirements

👤 User Management

Secure registration and login with role-based access for customers and movers

🔍 Service Discovery

Browse, search, and filter moving services by location, price, and ratings

📅 Booking System

Real-time booking flow with date selection, confirmation, and status tracking

⭐ Reviews & Ratings

Customer feedback system to build trust and quality assurance

🛠 Mover Dashboard

Service management, booking tracking, and profile customization for movers

📱 Responsive Design

Fully responsive interface that works across desktop, tablet, and mobile

Architecture & Design

Frontend (apps/web)

React SPA built with Create React App, featuring component-based architecture, React Router for navigation, and a clean responsive UI.

Backend (apps/api)

Node.js + Express REST API layer handling business logic, authentication, and data validation with Supabase as the data store.

Database & Auth

Supabase provides PostgreSQL-backed data persistence, user authentication, and real-time capabilities out of the box.

Project Plan & Timeline

Phase 1 Planning & Requirements

Project scoping, requirements gathering, user stories, and wireframe design

Phase 2 Design & Prototyping

UI/UX design, component mockups, database schema, and API contract definitions

Phase 3 Core Development

Frontend scaffolding, API endpoints, Supabase integration, and auth flow implementation

Phase 4 Feature Implementation

Booking system, search/filter, mover profiles, reviews, and dashboard features

Phase 5 Testing & Deployment

Integration testing, bug fixes, performance optimization, and final deployment

Team & my role

A team of 5 at George Brown College across frontend, backend, database, UI/UX, and DevOps. Built as a proof of concept — never launched commercially, and documented here in full. My part: Supabase auth (login flow + middleware), database connection and migrations, the Dockerized environment, and integrating the frontend/backend branches on main — pull requests and merge conflict resolution included. Top contributor with 24 of 51 commits.

Repository & commit history →

Design & implementation evidence

Figma Mockups

Full UI/UX design system and screen flows
Implementation Evidence

Annotated screenshots of the build
Coursework archive — project documentation

Technical Documents

Project Summary

Overview and scope of the Move-In platform
Project Vision

Goals, objectives, and long-term direction
Project Requirements

High-level business and functional requirements
Project Plan

Sprint planning, milestones, and deliverables
Requirements Analysis & Design

Detailed analysis, use cases, and design decisions
Wireframes & Mockups

Figma UI/UX designs and screen mockups
Status Report

Sprint progress and status updates
System Implementation

Implementation evidence with screenshots

Projects

01
RAG pipeline diagram: PDF to chunks to embeddings to ChromaDB to local LLM

Local PDF RAG

AI / Machine Learning

A local Retrieval-Augmented Generation pipeline that processes PDF documents, extracts text, chunks content, generates embeddings, and stores them in ChromaDB for semantic retrieval. Includes local LLM integration for context-based question answering.

PythonPyTorchHugging FaceChromaDBLangChainpdfplumber

Key Features:

  • PDF text extraction with intelligent chunking
  • Vector embeddings stored in ChromaDB
  • Semantic search with LLM-powered answers
View on GitHub →
02
Docker Compose diagram: React UI to Express API to MongoDB

Employee Management System

Full-Stack MERN + REST API

One system, two deliverables: a RESTful employee API (JWT auth, bcrypt hashing, express-validator input checks) and a Dockerized React front end with auth, CRUD, search, and profile image upload — built API-first, then wired to the UI.

MongoDBExpress.jsReact.jsNode.jsJWTDocker

Key Features:

  • JWT auth with bcrypt hashing & protected routes
  • Full CRUD with search and image upload
  • Docker Compose: app, API, Mongo Express admin
03
Regression schematic: housing values fit with a line

California Housing Price Prediction

Machine Learning

Implemented multiple linear regression from scratch using closed-form solution and gradient descent, then benchmarked against scikit-learn. Includes preprocessing, scaling, evaluation, and visualizations.

PythonNumPypandasmatplotlibscikit-learn

Key Features:

  • Regression from scratch vs scikit-learn comparison
  • Feature scaling and preprocessing pipeline
  • Evaluation metrics and result visualization
View on GitHub →
04
Classification schematic: retention prediction distribution

Telco Customer Churn Prediction

Machine Learning

A customer churn classification pipeline using logistic regression, including one-hot encoding, feature scaling, confusion matrix analysis, and threshold tuning. Also built logistic regression from scratch for comparison.

PythonNumPypandasmatplotlibscikit-learn

Key Features:

  • Logistic regression from scratch vs scikit-learn
  • Confusion matrix and threshold optimization
  • One-hot encoding and feature engineering
View on GitHub →

Get In Touch

The fastest way to reach me is through LinkedIn.

LinkedIn

linkedin.com/in/lakshay-dhawan

GitHub

github.com/imlakshayd