Full Stack Developer

Genius Innovation Lab; Canada; On-site; CAD 110,000 - 150,000; Full time

Job summary

A Canadian technology company seeks a versatile engineer for a dynamic role focused on creating MVP tools and integrating AI workflows. Candidates should be product-minded, thrive in fast-paced environments, and possess strong full-stack proficiency. Ideal applicants are curious, self-starting, and comfortable with ambiguity, leveraging modern AI tools to enhance productivity. Join a startup-style environment where innovation and rapid prototyping are key to success.

Qualifications

• Experience in startup-style environments with scaling knowledge.
• Ability to prototype quickly without sacrificing future scalability.
• Fluency in various programming languages and development tools.
• Experience or willingness to work with AI frameworks such as the Model Context Protocol, vector stores, prompt templates, and orchestration tools for LLMs.
• Mac is required, and ideally an iPhone so they can test lightweight iOS tools. Comfortable learning iOS basics via tools like Claude.

Responsibilities

• Build internal tools that enhance team productivity.
• Create MVP tools for experimental projects.
• Integrate AI workflows with backend functionalities.
• Backend services that interpret natural language commands, manage prompt flows, and orchestrate AI behavior through MCP or similar frameworks.
• Mobile convenience tools that act as thin clients for MCP‑driven backends, using voice, touch, or simple UI to interact with AI workflows.

Skills

Versatility in engineering

AI fluency

Full stack proficiency

Experience with MVP development

Prototyping ability

Comfort with ambiguity

Vector stores

Prompt templates

LLM orchestration

iOS basics

Claude

Tools

React

REST APIs

Model Context Protocol

Command line tools

Job description

We’re looking for a Swiss Army knife engineer. Someone highly versatile, curious, and product‑minded who thrives in a fast‑moving, experimental environment. This isn’t a role for someone who wants to go deep in one area. It’s for someone who wants to go wide, build useful things quickly, and constantly experiment.

https://geniusinnovationlab.careers-page.com/jobs/c141bffc-b2f9-472e-b4e0-cab44b281550

Job Responsibilities

This person will work on a variety of internal tools that improve team productivity and workflows. The majority of what they build will be MVP‑level tools that solve specific problems, often in experimental or fast‑evolving areas. Some examples include:

Voice‑driven mobile utilities, particularly on iOS, that use microphone input to generate structured actions through AI pipelines. These tools will use the Model Context Protocol (MCP) to convert voice commands into meaningful backend operations. For example, a voice input could control systems like Jira, Notion, or query email inboxes through structured prompts sent via MCP.

Backend services that interpret natural language commands, manage prompt flows, and orchestrate AI behavior through MCP or similar frameworks. This includes handling queries like "Did I get any emails from X?" and translating them into actionable AI tasks.

Mobile convenience tools that act as thin clients for MCP‑driven backends, using voice, touch, or simple UI to interact with AI workflows.

Salary will be based on experience

Mindset and personality

Inherently curious. They’ve built tools or side projects just for fun. They probably have a repo or folder full of scripts they’ve written to make their own life easier.

Loves building. They should have a hacker mentality, someone who enjoys making things work rather than waiting for specs.

Self‑starting and entrepreneurial. When given a loose idea, they can return with a working prototype and highlight edge cases or features no one asked about yet.

AI‑native. They must actively use and embrace modern AI tools like Claude, GPT, Copilot, etc., to move faster and be more effective. This is not the right role for someone who is skeptical of AI or thinks their expertise makes AI irrelevant. We believe AI is a multiplier, and this engineer should be fluent in using it across their work.

Comfortable with the unknown. Whether it’s building a Chrome extension, wiring up an iOS app, or connecting voice inputs to backend tools, they will be asked to figure things out on the fly.

Scale and tradeoffs

They must have experience working in both startup‑style environments and scaled systems. We need someone who understands the tradeoffs they’re making during fast prototyping, not someone who’s unaware of what’s missing or skipped. They should:

• Know how to ship something quickly and know what it would take to harden it later
• Be capable of outlining what scaling it up would look like, or guiding the hiring of the right people when it's time
• Be comfortable with MVP development, but have the background to spot technical debt and communicate clearly about it
• Have a healthy bias toward shipping, without being reckless about long‑term costs

Technical background

• Full stack proficiency, able to build from scratch and touch every part of the stack
• Experience with building backends, ideally REST or lightweight service‑based architectures. The systems don’t need to be over‑engineered for scale, but they should be reliable
• Familiarity with frontend frameworks like React. Experience with Chrome extension development is a plus
• Experience or willingness to work with AI frameworks such as the Model Context Protocol, vector stores, prompt templates, and orchestration tools for LLMs
• Mobile experience is not required, but they should be willing to experiment. A Mac is required, and ideally they use an iPhone so they can test lightweight iOS tools. They should be comfortable learning iOS basics via tools like Claude if needed
• Fluency with a range of languages and tools. Variety is more important than deep specialization
• Bonus for open source work, personal projects, or tinkering with things like home automation or Arduino. These signal a builder mindset and a willingness to play with unfamiliar platforms

Culture fit

• Thinks in terms of products and workflows, not just tasks or tickets
• Can operate in ambiguity and turn high‑level ideas into specific, working tools
• Comfortable switching between tasks or technologies frequently
• Communicates clearly and proactively, especially about risks, tradeoffs, or alternate ideas
• Energized by getting things done, trying new things, and solving real problems

This is someone who thrives in a zero‑to‑one setting, uses AI tools as an extension of their workflow, and wants to build practical tools that help others work faster. They don’t need to be an expert in any one area, but they do need to be fearless, fast, and thoughtful about how they work.