Job Description
Location: Mississauga, Ontario

Job Type: Full-time

Work Arrangement: Hybrid

Salary: CAD $85,000 - $120,000 per year

About the Role

As a Software Engineer - AI & Product Engineering, you will work at the intersection of software engineering, product development, AI, and real-world customer problems.

You will not simply be building features from a predefined list of requirements. You'll have opportunities to understand the problem, explore potential solutions, build them, test them, and improve them based on feedback.

We're open to both:

• Emerging developers with strong projects, academic work, or demonstrated ability to build; and
• Experienced software engineers who want broader product ownership and the opportunity to work with AI.

Your level of responsibility will grow based on your experience, capability, and demonstrated ownership.

What You'll Do

• Build and improve software solutions that address real customer and operational problems
• Work closely with Product and Engineering to understand requirements and develop practical solutions
• Develop, test, debug, and deploy software features
• Investigate data and customer problems to identify opportunities for improvement
• Use AI and modern development tools to accelerate research, development, testing, and problem-solving
• Participate in technical discussions, code reviews, and solution design
• Learn from customer and internal feedback and continuously improve solutions
• Take ownership of projects and deliver results with increasing independence

AI-First Engineering

AI is an important part of how we build at ZenduIT.

We encourage our engineers to use AI tools thoughtfully to improve research, coding, debugging, testing, documentation, analysis, and problem-solving.

You don't need to be an AI specialist. However, you should be curious about AI and comfortable experimenting with tools such as ChatGPT, Claude, GitHub Copilot, or similar technologies.

We value judgment over blind automation. You should be comfortable reviewing, validating, testing, and improving AI-generated work rather than simply accepting the output.

Technologies & Experience

Experience with some of the following is valuable:

• Angular
• Node.js
• MongoDB
• SQL
• REST APIs and integrations
• Data analysis and analytics
• Automation
• AI / LLM-powered applications
• Modern software development practices

You do not need experience with every technology listed above. We care more about your ability to learn, build, solve problems, and apply technology effectively.

Experience in SaaS, fleet management, telematics, IoT, connected vehicles, or operational technology is an asset but not required.

What We're Looking For

We're looking for someone who demonstrates:

• Builder Mindset - You enjoy creating, improving, and finding better ways to solve problems.
• Learning Agility - You can quickly learn new technologies, products, and concepts.
• Problem-Solving - You can break down ambiguous problems and develop practical solutions.
• Ownership - You take responsibility for your work and follow through to completion.
• Product Thinking - You care about why something is being built, not just how it is built.
• Curiosity - You ask questions and want to understand the underlying problem.
• AI Leverage - You are interested in using AI to become a more effective engineer.

Example of the Work

Imagine a fleet manager receives hundreds of maintenance alerts and struggles to identify which issues require immediate attention.

You might:

1. Investigate the underlying data and customer problem
2. Identify how alerts could be prioritized
3. Design and build a solution
4. Use AI to accelerate parts of the research or development process
5. Work with Product and Engineering to test the solution
6. Review feedback and improve the experience

The objective isn't simply to write code. It's to build something that solves a real problem.

How to Apply

Please submit your resume and, if available, an example of something you've built.

This could include:

• GitHub repository
• Working demo
• Personal or academic project
• Application or product you've built
• Screenshots
• Short case study
• Technical project you're proud of

If the work is confidential, you can provide a redacted explanation instead.

When sharing your work, we'd love to understand:

What problem were you solving? What did you personally contribute? How did you use AI or other tools? How did you validate the result? What did you learn?

You don't need a perfect project. We want to see how you think, build, learn, and solve problems.