Darsh is available for hire

Darsh Panchal

Verified Expert in Engineering

Software Engineer and Back-end Developer

Toronto, ON, Canada

Toptal member since April 21, 2025

Expertise

Python LLM Git PHP PostgreSQL Laravel Agile Development Docker Java AWS Machine Learning Deep Learning Multithreading Data Engineering RAG

Bio

Darsh is an experienced software engineer specializing in enterprise software and designing scalable architectures and AI-driven solutions. He has a proven track record of reducing data costs by 50% through cloud optimization, delivering reliable generative AI applications with LlamaIndex, and building high-performance big data engines using Spark and Kafka. Proficient in Python, Java, PHP, and GenAI integrations, Darsh consistently delivers secure, reliable, and scalable products.

Portfolio

Hitachi Cyber

Python, Java, PHP, FastAPI, Laravel, PostgreSQL, MongoDB, REST...

OkayG Softwares Pvt Ltd

Vue, Node.js, MySQL, OAuth 2, JSON Web Tokens (JWT), Selenium, Cypress...

Experience

Python - 5 years
FastAPI - 4 years
PHP - 4 years
PostgreSQL - 4 years
Amazon Web Services (AWS) - 2 years
Java - 2 years
LlamaIndex - 1 year
Apache Kafka - 1 year

Availability

Full-time

Preferred Environment

Slack, Teams, PyCharm, Visual Studio Code (VS Code), Windows, Linux

The most amazing...

...solution I've built is a GenAI RAG reporting system that converts client data into actionable insights using LLMs, enhancing report quality and visualizations.

Work Experience

Back-end Developer

2021 - PRESENT

Hitachi Cyber

Developed back-end microservices using FastAPI in Python and Laravel in PHP within a Docker environment, handling over 300,000 REST API requests daily and ensuring reliability and security throughout the development process.
Built a Python multithreaded microservice to integrate 3rd-party APIs and process over 100,000 security alerts daily, prioritizing concurrency in the design. The system reduced analysts' triage time by 30% by automating LLM-generated alert summaries.
Designed and developed a GenAI RAG-based reporting system that synthesized client data into actionable insights using LLMs and LlamaIndex, enhancing report quality and simplifying visualizations for stakeholders.
Collaborated with the solution architect and engineers to design and implement a big data engine that processes over 10 million events daily in real time, using Java, Kafka, and Spark, focusing on scalability and speed.
Migrated client data from on-prem PostgreSQL to Amazon Relational Database Service (Amazon RDS) and transitioned data from MongoDB to Amazon Athena, reducing data operation costs by 50%.
Co-led an Agile team, conducting daily scrums and resolving over 10 technical blockers per week to ensure 100% sprint completion.
Optimized LLM inference costs by 30%, maintaining 92% output quality through prompt engineering and migration to open-source models.
Designed a custom PHP testing framework that accelerated unit testing by 30%, achieving over 80% code coverage and ensuring stable, secure releases.
Collaborated with the DevOps team to containerize production microservices and design CI/CD pipelines using Docker and Jenkins, ensuring seamless, zero-downtime deployments.

Technologies: Python, Java, PHP, FastAPI, Laravel, PostgreSQL, MongoDB, REST, Amazon Web Services (AWS), Apache Spark, LlamaIndex, Apache Kafka, Docker, Jenkins, Git, Data Science, TensorFlow, C++, Deep Learning, Flask

Software Engineer

2018 - 2019

OkayG Softwares Pvt Ltd

Developed a full-stack application using Vue, Node.js, and MySQL, implementing JSON Web Token (JWT), OAuth 2.0, and multi-factor authentication (MFA), achieving 99.9% uptime.
Conducted comprehensive end-to-end testing in collaboration with the QA team using Selenium and Cypress, achieving 99.8% test coverage and reducing production bugs by 50%.
Engineered a scikit-learn machine learning model for image clarity detection with 99% accuracy and fine-tuned a ResNet50 neural network integrated with OpenCV to detect real-time user attention with 97% accuracy.
Implemented lazy loading techniques, reducing initial page load time by 30% and enhancing the user experience.

Technologies: Vue, Node.js, MySQL, OAuth 2, JSON Web Tokens (JWT), Selenium, Cypress, Scikit-learn, TensorFlow, OpenCV, Git, Machine Learning, REST

Experience

GenAI RAG Reporting System

Collaborating with security analysts to identify a high-impact GenAI use case, I developed a RAG-based reporting tool utilizing LLMs and LlamaIndex. This system converts client data into actionable insights, delivering enhanced reports and improved data visualizations for stakeholders.

GenAI-driven Enrichment System

I developed a high-performance Python microservice that utilizes multithreading and prioritizes concurrency to integrate 3rd-party APIs and process over 100,000 daily security alerts. By incorporating automated LLM-generated summaries, the system reduced analyst triage time by 30%. Additionally, I collaborated with front-end engineers to ensure seamless integration of the back-end service.

Big Data Engine

Collaborating closely with the solution architect and engineering team, I designed and implemented a high-performance big data engine capable of processing over 10 million events daily in real time. Leveraging Java, Kafka, and Spark, we prioritized scalability and speed throughout the development process.

Education

2019 - 2020

Master of Engineering Degree in Electrical and Computer Engineering

University of Windsor - Windsor, ON, Canada

2014 - 2018

Bachelor of Technology Degree in Mechatronics

Ganpat University - Gujarat, India

Certifications

MARCH 2021 - PRESENT

Deploying Scalable Machine Learning for Data Science

JANUARY 2021 - PRESENT

Deep Learning with TensorFlow

IBM

AUGUST 2020 - PRESENT

Machine Learning with Python: A Practical Introduction

IBM

Skills

Libraries/APIs

Vue, Node.js, Scikit-learn, TensorFlow, OpenCV

Tools

Git, Slack, PyCharm, Jenkins, Plotly

Languages

Python, PHP, Java, C++, Embedded C

Paradigms

REST, Agile

Frameworks

LlamaIndex, Laravel, Apache Spark, OAuth 2, JSON Web Tokens (JWT), Selenium, Cypress, Flask

Platforms

Amazon Web Services (AWS), Docker, Apache Kafka, Visual Studio Code (VS Code), Windows, Linux

Storage

PostgreSQL, MongoDB, MySQL

Other

FastAPI, Generative Artificial Intelligence (GenAI), Large Language Models (LLMs), System Design, Teams, Data Science, Data Engineering, Machine Learning, Deep Learning, Retrieval-augmented Generation (RAG), Multithreading, Microcontrollers, Cryptography, Robotics

Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.

Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring