Python Full-stack Developer - Toronto, ON - Fulltime Opportunity

Zodiac Solutions; Toronto; Hybrid; CAD 110,000 - 170,000; Full time

Job summary

Zodiac Solutions in Toronto is seeking a Python full-stack developer with 8+ years of experience to design, build, and maintain scalable web applications using Python, Django/Flask/FastAPI, and React.

You will collaborate with product and data science teams to integrate AI/LLM features, develop robust APIs, and ensure performant database design across Postgres and SQL Server in a cloud environment.

Qualifications

• Bachelor's degree or Diploma in IT with equivalent experience.
• Proficient in Python and Django framework.
• Experience with LLMs and AI agent development.
• Strong React frontend skills and SQL database design.

Responsibilities

• Design, develop, test, and maintain full-stack web apps using Python and React.
• Build backend services, APIs, and business logic with Django/Flask/FastAPI.
• Develop responsive frontend interfaces with React, JS/TS, HTML, CSS.
• Integrate AI/ML features including LLMs, chatbots, recommender systems.
• Collaborate with product managers, designers, data scientists, and engineers.
• Design and optimize PostgreSQL/SQL Server databases for performance.
• Follow secure, reusable coding practices and CI/CD pipelines.
• Build/consume RESTful APIs and third-party integrations.
• Participate in architecture discussions, code reviews, and debugging.
• Support deployment, monitoring, and troubleshooting in cloud/production.

Skills

Python

Django

React

PostgreSQL

SQL Server

APIs

AI/ML

LLMs

DevOps CI/CD

Git

Education

Bachelor's degree in computer science or Diploma in IT

Tools

Docker

Kubernetes

LangChain

AutoGen

AWS/Azure/GCP

Git

Job description

Role: Python Full-stack Developer

Location: Toronto, ON(4 days hybrid)

Duration: Fulltime Opportunity

Exp: 8+ years

Responsibilities:

• Design, develop, test, and maintain full-stack web applications using Python and React.
• Build robust backend services, APIs, and business logic using frameworks such as Django, Flask, or FastAPI.
• Develop responsive, user-friendly frontend interfaces using React.js, JavaScript/TypeScript, HTML, and CSS.
• Integrate AI/ML capabilities into applications, including APIs, LLM-based features, chatbots, recommendation systems, or intelligent workflows.
• Collaborate with product managers, designers, data scientists, and other engineers to translate business requirements into technical solutions.
• Design and optimize relational and/or NoSQL databases for performance and scalability.
• Implement secure, reusable, and maintainable code following best practices and coding standards.
• Build and consume RESTful APIs and third-party integrations.
• Participate in architecture discussions, code reviews, debugging, and performance optimization.
• Support deployment, monitoring, and troubleshooting of applications in cloud or production environments.
• Stay current with emerging technologies in full-stack development and applied AI.

Requirements:

• Bachelor's degree in computer science or Diploma in IT with equivalent experience.
• Advance proficiency in Python and Django Framework
• Extensive experience with Large Language Models (LLMs)
• Proven experience in AI agent development and implementation
• Advance proficiency in React ecosystem
• Advanced proficiency with Postgres SQL
• Extensive experience with SQL server & database design
• Strong knowledge of front-end technologies such as React
• Experience with agent frameworks and orchestration platforms
• Knowledge of prompt engineering and LLM optimization techniques
• Understanding of AI agent architectures and design patterns
• Knowledge of design patterns & best practices in software development
• Experience with version control system such as Git
• Strong knowledge of working with API's.
• Familiarity with DevOps practices and CI/CD pipelines
• Strong communication skills

Preferred skills:

• Capital markets experience
• Experience with LangChain, AutoGen, or similar agent frameworks
• Knowledge of machine learning and deep learning concepts
• Familiarity with cloud platforms (AWS, Azure, GCP)
• Experience with containerization (Docker, Kubernetes)
• Knowledge of natural language processing (NLP) techniques
• Experience with streaming and real-time data processing
• Understanding of AI safety and responsible AI practices
• Experience with MLOps and model deployment pipelines