What We're Looking For:

Engineering

• 8–10 years of full stack engineering experience, including time spent owning systems in production at meaningful scale
• Deep expertise in React and Next.js, with a strong point of view on component architecture, state management, and performance
• Strong backend chops in Node.js — you've designed and operated services, not just built features inside them
• Advanced PostgreSQL — schema design, query optimization, migrations under load, multi-tenant patterns
• Production experience with auth/RBAC systems, especially in multi-tenant B2B contexts
• Hands-on experience with BullMQ or comparable queue/job systems (Sidekiq, RabbitMQ, SQS, Temporal) — and a clear sense of when to reach for them vs. simpler patterns

AI-Native Dev

• Hands-on experience building and running AI agents that do verifiably correct work. You design the guardrails that make agent output trustworthy: test suites and type checks the agent must pass, eval harnesses, golden datasets, self-verification loops, and human-review checkpoints where they matter. You can explain how you know an agent’s work is right, not just that it looks right
• You use AI coding agents as a core part of your daily workflow, not occasionally. You can walk us through how you delegate work to agents, what you hand off vs. keep, and how you verify the output
• Sharp judgment as the final reviewer. You catch subtle bugs, security issues, and bad architectural suggestions that slip past automated checks, and you know when an agent is confidently wrong
• You’ve shipped LLM-powered features to production: prompt design, structured outputs, tool use, and handling failure modes like hallucination, malformed responses, rate limits, and cost overruns
• You think about evals. You can define what “good” looks like for an AI feature and measure it rather than eyeballing it
• Familiarity with the current AI tooling landscape (agent frameworks, MCP, model APIs from Anthropic/OpenAI/others) and strong opinions about what’s useful vs. hype
• Bonus: you’ve built internal tools, agent workflows, or context systems that made a whole team more productive with AI

Product

• A real product brain. You can be handed a fuzzy customer problem and come back with a scoped, shippable plan - not a Jira ticket asking for specs
• Strong product taste. You push back on bad designs, come up with better ones, and have opinions about what "good" looks like in B2B software
• Customer instinct. You actually want to talk to users, watch them work, and let what you learn shape the product. You don't need to be shielded from messy customer feedback
• Ability to make tradeoff calls — what to cut, what to defer, what to over-invest in — without needing a PM to break the tie

Why Join Us:

• Profitable and growing
• Fast iteration, direct collaboration with founders, and unfiltered customer feedback
• Highly competitive salary and comprehensive health benefits

Hiring Process

• Initial call with our founding engineer to discuss your background and introduce SalesJack (~30 mins)
• Technical Exercise: Product Design, Live coding and problem-solving session (~2.5 hours, might be 2 separate sessions) - this might be in person in our Toronto office
• Product and culture call with one of our founders (~30 mins)
• Offer

Compensation: CA$160K - CA$200K