0
Publications
0
Followers
0
Following
0
Questions
About
Pronoy Chopra is a seasoned technologist and innovator with over 15 years of experience in software engineering, solutions architecture, and AI/ML systems development. His professional journey spans a diverse range of sectors including neuroscience, telecom, agriculture technology, and cloud computing. Currently serving as a Senior Solutions Architect in AI/ML at Amazon Web Services, Pronoy has played a pivotal role in securing $400M in business opportunities by leveraging advanced Generative AI platforms. He has built robust, serverless AI tools using Amazon Bedrock and Claude3, contributed significantly to AWS global outreach through conferences and blogs, and holds an AWS Machine Learning Specialty certification.
Pronoy’s background as a Principal Software Engineer at Kernel showcases his deep technical expertise in neuroscience and embedded systems. At Kernel, he engineered real-time data acquisition systems, optimized high-performance computing pipelines, and led the development of distributed control and visualization platforms. His ability to bridge hardware and software domains is evident in his contributions to camera integration, neuroscience simulation frameworks, and centralized data infrastructures.
Earlier in his career, Pronoy held impactful roles in the telecom sector, contributing to VoIP platforms and custom PBX solutions. His academic roots in electronics and communication engineering laid the foundation for his hands-on experience with embedded systems, AVR/RISC architectures, and control systems. Notably, he is the inventor of a patented wireless mesh network system tailored for agricultural applications and has contributed to the Google Summer of Code program.
Pronoy’s resume highlights his multidisciplinary expertise, innovative mindset, and leadership in scaling engineering teams and projects. He has developed numerous backend and frontend systems using technologies like Django, FastAPI, Flask, React, and Rust. His cloud and deployment capabilities span AWS services, Docker, Celery, and other DevOps tools. He also possesses a strong academic background with a Master’s in Electrical & Computer Engineering from the University of Oklahoma, where he worked on image retrieval systems and control automation.
Through public speaking engagements, hackathons, open-source contributions, and mentoring, Pronoy continues to impact the broader tech ecosystem. His unique ability to fuse low-level programming with modern cloud-native architecture makes him a rare hybrid engineer capable of solving complex challenges across domains.
Pronoy Chopra is a highly accomplished software engineer and solutions architect with over 15 years of diverse experience across software development, AI/ML systems, neuroscience technology, IoT, and cloud computing. Known for bridging low-level embedded systems with cutting-edge cloud-native platforms, Pronoy brings a rare combination of hardware proficiency and software architecture expertise that enables him to tackle some of the most complex challenges in the technology space.
Currently serving as a Senior Solutions Architect for AI/ML at Amazon Web Services (AWS), Pronoy has directly influenced over $400 million in business opportunities through his contributions to large-scale AI/ML initiatives. He is credited with building and maintaining internal ChatGPT-like tools using serverless architecture powered by Amazon Bedrock and Claude3 models. His work extends beyond technical implementation—he is a frequent speaker at AWS events like re:Invent and re:Inforce and has authored widely-read technical blogs on Generative AI, IoT, and cybersecurity. Pronoy also holds an AWS Machine Learning Specialty certification and is a core member of the AI/ML and IoT technical communities within AWS.
Before joining AWS, Pronoy was the Principal Software Engineer at Kernel, a pioneering neuroscience company focused on developing next-generation brain-computer interfaces. There, he was instrumental in integrating high-speed cameras for neural data capture, optimizing simulation pipelines using AWS and Docker, and creating centralized data infrastructures that cut operational costs by thousands of dollars monthly. His technical leadership led to the creation of a live dashboard in React and Flask for GPU and EC2 monitoring, a neuroscience task-runner using Django and Celery, and the migration of company-wide analysis workflows to JupyterLab, thereby significantly increasing efficiency.
Earlier in his career, Pronoy worked in the telecommunications sector at Apeiron Systems, where he contributed to building a Twilio-like Telecom-as-a-Service platform. His responsibilities included working with vendor APIs (e.g., Verizon, AT&T) and debugging complex VoIP and packet drop issues. Pronoy also served as a freelance consultant and product inventor in the agri-tech space, developing mesh network-based smart farming systems and delivering sustainable software solutions for governmental projects in India.
His academic background is equally impressive, with an MS in Electrical & Computer Engineering from the University of Oklahoma, where he worked on content-based image retrieval systems and automation tools using Python and LabView. He also holds a Bachelor’s in Electronics & Communication Engineering and has published and patented technologies in areas ranging from wireless networks to AI/ML optimization.
Throughout his journey, Pronoy has remained committed to innovation and education—hosting public hacking sessions, mentoring teams, and scaling engineering departments. His technical skill set spans Python, JavaScript, C++, Rust, Flask, Django, AWS, Docker, Celery, PostgreSQL, Redis, and more. He is also experienced in embedded systems programming, scientific computing, and full-stack development.
In essence, Pronoy Chopra exemplifies the modern technologist—deeply technical, highly innovative, and capable of navigating and integrating across the full technology stack, from microcontrollers to machine learning APIs.
Skills & Expertise
AWS
Docker
C++
JavaScript
Python
Labview
PostgreSQL
NoSQL
Git
Nginx
React Native
React
Redis
Django
Supervisor
Supervisor
Flask
AWS CDK
Rust
Lua
FastAPI
Celery
RabbitMQ
SQLAlchemy
JupyterLab
PyQt
Typescript
Psychopy
Fabric
Gunicorn
uWSGI
AVR/RISC
LSF
Electron
mDNS/Bonjour
Upstart
Javascript (React/React-Native)
Lua
C++
Basic Rust
Django
Flask
jQuery
Memcached
Celery
Requests
Django-Rest-Framework
Redis
NoSQL
DAL/ORM (SQLAlchemy
Django ORM
Diesel)
RabbitMQ
SVN
GIT
upstart
Avahi
mDNS/Bonjour
UFW
Fabric
Nginx
Gunicorn
uWsgi
LAMP
AWS
low level IoT programming
Research Interests
Cybersecurity
Embedded Systems
Generative AI
Data Engineering
Human-Computer Interaction
Serverless Computing
Cloud Solutions
AI/ML Architecture
Neuroscience Interfaces
IoT Applications
Scientific Computing
DevOps and Automation
Edge Computing
Connect With Me
Experience
Senior Startups Solutions Architect - Generative AI
- Senior Startups Solutions Architect - Generative AI Nov 2024 - Present · Senior Startups Solutions Architect - AI/ML Mar 2021 - Feb 2025 · Los Angeles, California, United States ● Solutions Architect directly responsible and contributed to closing opportunities worth $400M over the course of three years in the Generative AI and Machine Learning space. ● Built, deployed, marketed and maintained an internal ChatGPT like utility on a complete serverless platform with Amazon Bedrock and Claude3 models ● Speaker at multiple re:Invent, re:Inforce and Generative AI sessions and conferences. ● Authored multiple global blogs on IoT, Machine Learning, GenerativeAI, Cybersecurity with global outreach. ● Machine learning specialty certification and member of the IoT and AI/ML technical field community within Amazon.
Principal Software Engineer
- C/C++, Python, Rust, React, PyQt5, Qt5 and whatever else it takes ● Hired as the first Software engineer @ Kernel ● Unblocked integration of high speed cameras built on GeniCam spec with PCIe frame grabber boards to acquire 16 channels simultaneously using C++ with python bindings. ● Advised and architected a solution on AWS to speed up MCX (monte carlo extreme) simulations using celery, docker and S3, resulting in avg $9K savings per month ● Built a React based live dashboard to get information about task queue, gpu usage and current ec2 instance stats through a Flask based server for the modeling team ● Synced with various internal teams and built a distributed control system connecting multiple computers/SoC boards connected to DAQs. ● Delivered an initial version of a control/graphing UI in PyQt and then further migrating to an electron based app for company wide deployment and control. ● Created a central data repository and brought compute in-house eliminating recurring costs by $8K every month. ● Migrated control UI to a centralized system (Typescript & Rust) and helped migrate everyone to Jupyterlab instead of individual machines reducing analysis times drastically. ● Help standardize neuroscience tasks by building an API for animations, data/events streaming and layout using Psychopy ● Built a task-runner system and API to launch jobs against data sets using Django, celery, Docker and LSF which allowed teams to run data transforms to feed into pyspark pipeline thereby eliminating repetitive tasks ● Routinely instruct, advise and help optimize scientific codebase (Python) to reduce runtime and memory usage. ● Hired key software team members and expanded team from 1 to 15 people ● Helped standardize the data format and enabled multiple teams integrate their custom devices into our control system thereby reducing complexity in conducting experiments ● Optimized image recognition and extraction thereby helping protect medical data and identity ● Currently Helping the team deliver NaaS prototype (neuroscience as a service) on AWS using python serverless architecture (AWS Chalice)
Software Engineer III
- ● Twilio like Telecom-as-a-service built using Django + React + React-Native ● Interfaced with various vendor APIs like Verizon, AT&T etc. for number service provisioning ● Built, debugged and helped troubleshoot various packet drop issues ● Experience with soft switches and software defined telecom stacks like Freeswitch to create custom PBXs
Hardware/Software Engineer
- Built small sensor networks that allow farmers to calculate ROI over variables like water intake, uv index, lux and similar factors. With the recent drought in CA, it was our intention to create mesh networks to accurately map what factors would lead to a better yield. Django based API server with complete frontend design
Software Developer
- Web and native app development using Django and other python tools.
Graduate Research Assistant
- Python developer and Web application architect
DEVELOPER
- I created a web portal using Python Flask and Mongo DB. I managed servers and DNS entries. I also created a research tool for repertory grid technique using the same technologies. I have worked extensively with Ajax and javascript and am currently heading the web development initiative at the Rural Housing Knowledge Network sanctioned by the Ministry Of Rural Development (Govt. Of India). This is a national level project.
Contractor
- Developed and delivered a Asset Management System for WorldForge MMORPG built using Flask + Ogre3D game engine and a lot of javascript. I created the a web based asset management system using Python and created a 3D asset viewer. I worked on C++ as well, to render the 3D assets in Ogre3D. It was probably one of the best learning experiences I've had.
Education
University of Oklahoma (OU)
Jaypee University Of Information Technology (JUIT)
Projects
Never Alone
This game was designed and partially developed for Ludum Dare 22 gamedev sprint competition. As the design was considered potent, the game is still in development.
Certificates & Licenses (1)
AWS Certified Machine Learning - Specialty
Credential ID be8b6ea6-ea46-4ec9-b7ff-c82d8be02ff7
https://www.credly.com/badges/be8b6ea6-ea46-4ec9-b7ff-c82d8be02ff7
Earners of this certification have an in-depth understanding of AWS machine learning (ML) services. They demonstrated ability to build, train, tune, and deploy ML models using the AWS Cloud. Badge owners can derive insight from AWS ML services using either pretrained models or custom models built from open-source frameworks.
Patents (1)
Wireless Sensor Mesh Network With Dual Homed Router & Control Through Mobile Devices
description
dd