AI Product Builder — IoT & Data Intelligence

GoFleet • Mississauga, ON

22d • CA$50,000 - CA$125,000

About The Position

Zenduit Product Developer / Engineer
Role intent: This role is designed for Zenduit’s shift from ticket-driven development to product-driven engineering. The Product Developer / Engineer owns a bounded product problem from understanding context to shipping, validating, and iterating. The role blends strong engineering execution with product judgment, customer awareness, and self-owned quality.
About Zenduit
Zenduit is an AI-enabled SaaS company focused on telematics, fleet management, and connected operations. We build intelligent systems that combine software, data, automation, hardware, and operational workflows. Our culture is execution-first: we value builders who can understand the real business problem, move quickly, and ship solutions that create measurable value.
Role Summary
Product Developers / Engineers are product-minded builders. They do not wait for perfectly detailed tickets or throw work over the wall for others to validate. They think beyond tickets, understand the customer and product context, identify edge cases and failure modes early, own testing and production readiness, use AI for leverage without lowering standards, and improve the system rather than only completing assigned work.
In bounded product areas, this role performs work traditionally split across product management and engineering: problem framing, scope definition, acceptance criteria, implementation, validation, release, and iteration. For larger initiatives, the Product Developer / Engineer partners with design, leadership, and other specialists while still owning technical-product judgment for their area.
What Good Looks Like
Thinks beyond tickets and asks better questions before building.
Understands the customer workflow, business context, and product constraints.
Can take an ambiguous problem and turn it into a safe, shippable solution.
Owns self-QA: tests, validation, observability, release readiness, and post-launch follow-up.
Uses Claude Code expertly to accelerate development, documentation, debugging, refactoring, and test creation.
Makes stronger technical decisions with less dependence on over-detailed specs.
Improves the system: architecture, tooling, workflows, reliability, and developer leverage.
AI Usage Statement
At Zenduit, we actively leverage AI and automation tools to improve efficiency and decision-making across finance operations. This role will involve working with AI-powered systems for workflow automation, anomaly detection, and reporting.

Requirements

• 2 or more years of experience in full-stack engineering, product engineering, or a closely related build-heavy role.
• Strong experience with TypeScript/JavaScript and modern web application development.
• Strong experience with Angular, Node.js, MongoDB, REST APIs, Git, and debugging across frontend and backend layers, or equivalent ability in a closely related stack.
• Proven ability to move from ambiguous problem to shipped solution with minimal reliance on step-by-step specs.
• Strong testing instincts and hands-on experience with automated testing, release validation, and production troubleshooting.
• Demonstrated product judgment: can connect technical decisions to customer value, business context, and operational impact.
• A strong candidate for this role should already demonstrate practical, high-trust use of Claude in development work. At Zenduit, “good with Claude” does not mean generating code blindly. It means using Claude deliberately to increase speed, understanding, and quality while keeping human ownership of decisions and verification.
• Can use Claude to understand an unfamiliar codebase, propose an implementation plan, and identify likely edge cases.
• Can create or improve project instructions so Claude follows the repo’s standards consistently.
• Can use Claude to generate tests, refactor code, draft PR summaries, and accelerate debugging without skipping understanding.
• Can keep sessions scoped and context clean, and knows how to recover when the model starts drifting.
• Can explain what they accepted from Claude, what they rejected, and why.
• Bonus: can use Claude with external tools, automations, or validation workflows to reduce repetitive engineering work.

Nice To Haves

• Experience in SaaS, IoT, telematics, fleet management, or connected operations.
• Experience building internal tools, automations, or AI-assisted workflows.
• Exposure to analytics, event instrumentation, and experimentation.
• Experience with agentic workflows, MCP-style integrations, or code-generation guardrails.

Responsibilities

• Product Context and Problem Framing: Understand the customer workflow, business goals, product metrics, and operational context behind each initiative. Translate ambiguous requests or rough ideas into clear hypotheses, acceptance criteria, edge cases, and implementation options. Talk to the right stakeholders early, including support, sales, operations, or end users when needed. Challenge weak solutions and propose better alternatives based on value, feasibility, and risk.
• End-to-End Solution Ownership: Own a bounded product area from problem definition through implementation, validation, release, and iteration. Take initiative on low- and medium-risk product changes without requiring hand-holding. Drive delivery by decomposing work, sequencing decisions, and escalating only the right risks. Treat delivery as outcomes shipped, not tickets completed.
• Hands-on Product Development: Build across frontend, backend, APIs, integrations, and data flows using Zenduit’s stack or equivalent modern web technologies. Write maintainable code that balances speed with clarity, scalability, and future changeability. Contribute to architecture and data-modeling decisions, especially where product behavior and system behavior intersect. Use instrumentation and telemetry to verify product behavior in production.
• Quality Ownership and Self-QA: Own the quality of every change: unit, integration, regression, and risk-based validation. Define a test strategy for the level of risk involved, not just the happy path. Identify edge cases, failure modes, rollout risks, rollback options, and operational implications before release. Improve automation coverage, debugging workflows, and release confidence over time.
• AI-Native Development with Claude Code: Use Claude Code as a primary development accelerator for codebase exploration, implementation planning, code generation, refactoring, debugging, test generation, documentation, and PR preparation. Maintain strong project context for Claude using repo instructions, conventions, and repeatable workflows. Know when to trust Claude for speed and when to slow down for human verification, especially on risky or customer-facing changes. Create reusable leverage for the team through prompts, scripts, instructions, automations, or integrations rather than relying only on one-off chats.
• Cross-Functional Collaboration: Collaborate directly with product, design, support, operations, and leadership where it improves speed or solution quality. Communicate trade-offs, assumptions, open questions, and risks clearly. Use support and customer feedback to shape fixes, usability improvements, and prevention work.
• Continuous Improvement and Adjacent Value: Use time saved by AI to increase value, not reduce ownership. Automate repetitive work and contribute reusable internal tools, workflows, templates, and playbooks. Spot system-level improvements that save time, reduce defects, improve customer experience, or increase team output.

Benefits

• Build a modern, AI-enabled finance function from the ground up
• Work on real operational complexity (SaaS + hardware + global pricing)
• Direct impact on business efficiency, margins, and scalability
• Opportunity to shape the future of finance operations in a high-growth environment

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed