Company overview Birdseye’s mission is to help make the world a safer place

We are the leader in AI-driven Remote Facility Supervision solutions for the Trucking and Logistics Industry. Our Maximum Telepresence Approach™ delivers cutting-edge, data-driven security and operational insights that create a safer working environment for millions of people every year.

We provide end-to-end, cutting-edge hardware and AI-driven solutions, redefining security beyond traditional gatehouses. By empowering our professionally trained monitoring agents, we achieve 99.99% reporting accuracy in mission-critical security, safety, and operational support -24/7/365- for some of the world’s largest logistics facilities, as well as small and medium-sized businesses.

If you’re ambitious, thrive in a fast-paced environment, and align with our ICARE values, Birdseye will be the perfect fit for you. If you’re wondering what the world will look like in 10 years - join our Team

Role We are looking for a Full Stack Developer who can build production software across the front end and back end.

This needs to be an AI-native developer. We are not looking for someone who has merely tried ChatGPT, Copilot, or Claude. You should have fundamentally changed how you develop software using agentic tools such as Claude Code, Cursor, or equivalent tools. The candidate must be strong with React and Redux on the front end and Java with Spring Boot on the back end. You should also be productive with either Node.js or Python.

Technology profile Front end Strong production experience with:

React

Redux

Responsive web applications

Component-based interface design

Complex state and workflow management





API integration

Automated front-end testing

React and Redux depth is particularly key. The candidate should understand how to keep state, components, and user workflows maintainable as an application grows.

Back end Strong production experience with:

Java

Spring Boot

REST APIs

Service and business-logic design

Relational databases

Authentication and authorization

Integration and automated testing

Production troubleshooting

You should also be productive with at least one of:

Node.js

Python

Java and Spring Boot remain the primary back-end requirement. Node.js or Python expands the candidate's ability to build supporting services, automation, developer tooling, tests, and integrations.

AI-native engineering This is a must-have, not a nice-to-have.

The candidate should use AI throughout the entire software-development lifecycle, including:

Turning requirements into specifications

Exploring and understanding existing codebases

Evaluating architecture and implementation options

Writing and refactoring code

Reviewing code and pull requests

Creating automated tests

Performing QA

Reproducing and debugging defects

Writing technical documentation

Preparing and validating releases





Your AI toolbox should extend beyond autocomplete inside an IDE. You should be comfortable using agentic command-line tools, repository-level instructions, automated browser and test tooling, and other development capabilities outside the traditional IDE.

You should understand how to:

Break substantial work into bounded assignments for subagents

Run independent investigations or implementation tasks in parallel

Give each agent the right context and constraints

Manage dependencies between agents

Reconcile multiple outputs into one coherent implementation

Identify conflicting assumptions or missing integration points

Manage the context window deliberately

Summarize long-running work without losing important decisions

Recognize when context has become stale or overloaded

Validate AI-produced work before it reaches production

The candidate remains accountable for everything that AI produces. AI mastery does not replace technical judgment.

What you would own

Front-end implementation: Build clear, responsive React and Redux interfaces for complex operational workflows.

Back-end implementation: Build APIs, integrations, and business logic using Java and Spring Boot.

AI-native execution: Use agents throughout specification, implementation, review, testing, debugging, and documentation.

Automated quality: Create meaningful unit, integration, API, and front-end tests.

Production readiness: Consider failure handling, observability, security, performance, and maintainability before release.

End-to-end delivery: Stay responsible for the capability after the initial code is wri

📌 Full Stack Developer (Mississauga)
🏢 Birdseye Solutions
📍 Mississauga