AI • Cloud • Backend

AI / Cloud / Backend Engineer · Toronto, Canada

Building reliable AI, cloud, and backend systems for real-world operations.

I create production-minded software across machine learning, API engineering, automation, and cloud infrastructure. My focus is turning complex technical ideas into secure, measurable, and scalable systems.

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Toronto, ON Open to AI, cloud, and backend roles Python · AWS · FastAPI · ML
95% Image classification accuracy
100+ Concurrent inference requests
25% Execution speed improvement

I work across the complete delivery path: model experimentation, API development, automation, deployment, monitoring, and iteration. The goal is not only to build working software, but to build software that is clear, maintainable, and ready for production use.

Machine Learning Cloud Infrastructure Automation Fintech Systems APIs and Backend CI/CD Delivery

Experience

Backend engineering with a focus on scale, security, and operational reliability.

I build production-ready systems that combine backend architecture, cloud-native deployment, security controls, and observability so applications can perform reliably under real traffic.

Cloud and backend Apr 2025

Software Engineer - Cloud and Backend

FastAPI, Node.js, AWS Lambda, API Gateway, OAuth 2.0

  • Engineered a distributed backend ecosystem with FastAPI and Node.js for real-time monitoring and automated scheduling workflows.
  • Designed serverless AWS Lambda and API Gateway infrastructure for elastic scaling, cost efficiency, and high-volume request handling.
  • Strengthened platform security with an identity-driven model built around OAuth 2.0 and RBAC.
  • Improved reliability with Docker-based deployment, structured logging, observability tooling, and failover recovery patterns.

Projects

Selected projects built around measurable outcomes and production constraints.

These projects emphasize throughput, latency, reliability, deployment design, and clear engineering tradeoffs.

August 2024 ML service

Machine Learning Engineer - Image Classification Service

A high-throughput computer vision service designed for accurate inference and cost-effective serverless scaling.

CNNs Classical ML FastAPI AWS Lambda S3 Computer Vision Async Inference
  • Architected an end-to-end image classification pipeline combining advanced CNN architectures with classical ML models.
  • Achieved 95% classification accuracy while supporting 100+ concurrent requests with sub-2-second inference latency.
  • Developed an asynchronous FastAPI microservice and a serverless inference flow using AWS Lambda and S3.
  • Applied cold-start optimization techniques to improve responsiveness and operational efficiency in production.
Sep 2024 Distributed platform

Distributed Scheduling and Monitoring Platform

A multi-user orchestration platform for real-time availability tracking, notifications, and resilient automated execution.

PostgreSQL AWS Lambda Real-time Monitoring Notifications Session Management Failover Strategy Distributed Workflows
  • Architected a multi-user scheduling and monitoring platform for real-time availability tracking and automated workflow orchestration.
  • Built a persistent, timezone-intelligent engine with PostgreSQL and AWS Lambda to optimize execution windows and support zero-downtime horizontal scaling.
  • Implemented a high-performance notification layer that delivered sub-second responses through messaging APIs.
  • Added persistent session management and failover strategy to improve resilience across distributed environments.

Skills

Technical skills for models, APIs, infrastructure, automation, and delivery.

Programming

Core languages I use to build systems, automation, and backend services.

Python Java C++ Bash

AI and data

Libraries and frameworks I use for data processing, training, and visual analysis.

NumPy Pandas Scikit-learn TensorFlow PyTorch Keras OpenCV Matplotlib Seaborn

Cloud and DevOps

Platforms and delivery tools I use to deploy, automate, and maintain systems.

AWS Azure Google Cloud vSphere Docker Kubernetes Terraform CloudFormation Jenkins Ansible GitLab CI

Web, database, and tooling

Supporting technologies I use when turning models and services into usable products.

HTML CSS JavaScript Flask MySQL SQLite Git Selenium Appium Apache Guacamole DataSpell

Education

Academic grounding in artificial intelligence, virtualization, cloud, and core IT systems.

05 2025 Nova Scotia, Canada

Nova Scotia Community College

IT Programming for Artificial Intelligence

GPA: 3.5
08 2024 Ontario, Canada

Conestoga College

Virtualization and Cloud Computing

GPA: 3.46
06 2021 Vadodara, India

Sigma University

Bachelor of Information Technology

GPA: 3.6

Contact

Open to teams building practical AI, cloud, automation, and backend products.

I am interested in opportunities where I can contribute to reliable engineering, measurable product impact, and modern cloud-based delivery across AI-driven systems and backend platforms.

Best fit

AI engineering, cloud engineering, automation, backend systems, and information technology roles that value both experimentation and reliable execution.

Location

Toronto, ON

Availability

Open to remote, hybrid, and on-site opportunities.

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