Founding Engineer

Untrap is a venture-backed AI platform that helps businesses recover revenue they didn’t know they were losing. We have over 10 AI agents in production and we use large language models to transform operational data into actionable financial and business insights, giving companies visibility they’ve never had before.

We have paying customers, strong product‑market fit, and fresh funding. Now we’re hiring our first two engineers to accelerate product development and scale the platform.

You will be our first engineering hire and the technical backbone of the product. This is a hands‑on, full‑stack builder role, not a management title. You will ship production code weekly, contribute across the entire stack, and serve as a force multiplier as we grow the team to three engineers over the next twelve months.

You will have meaningful ownership of the codebase, direct influence over architecture decisions, and the opportunity to shape engineering culture from the ground up.

• Platform Reliability & Engineering Excellence: Strengthen the existing codebase through improved test coverage, CI/CD pipelines, monitoring, and deployment practices. Bring production‑grade discipline to a fast‑moving startup environment.
• Feature Development: Design, build, and ship customer‑facing features end‑to‑end, from backend data processing and AI‑powered insights to front‑end dashboards and reporting.
• LLM Integration & AI Engineering: Architect and optimise our AI pipeline including prompt engineering, retrieval‑augmented generation (RAG), model evaluation and training, and inference cost management across our cloud service providers.
• Production Support: Own the operational health of the platform. Triage issues, maintain uptime, and ensure our customers experience a reliable product.
• Technical Decision‑Making: Evaluate trade‑offs, recommend tooling, and make pragmatic architecture choices that balance speed with long‑term scalability.

• 5–7 years of professional software engineering experience, with demonstrable work shipping and scaling SaaS products used by real customers.
• Strong full‑stack proficiency:
  Python (backend), Next.js/React (frontend), and modern cloud infrastructure (AWS primarily, Azure secondarily).
• Experience building AI‑powered products for B2B or professional services verticals.
• Deep, hands‑on experience with large language models in production including prompt engineering, RAG pipelines, embeddings, model training and evaluation, and cost optimisation.
• Experience stabilising and improving early‑stage codebases: refactoring, adding observability, building CI/CD, and establishing engineering best practices.
• Solid understanding of SaaS business fundamentals including multi‑tenancy, billing, customer lifecycle, and the relationship between engineering decisions and business outcomes.
• Self‑directed problem solver who thrives with minimal supervision and can context‑switch across the stack.
• Located in Canada with the ability to meet in‑person 1–2 times per month.

• Familiarity with operational platforms such as PSA, ERP, or CRM systems and their data models.
• Prior experience as an early engineer at a funded startup.

• Competitive cash compensation plus equity in a venture‑backed company.
• Salary range for this role is between $102,000 and $115,300.
• Full‑time position; open to contract‑to‑hire for the right candidate.
• Hybrid: primarily remote with 1–2 in‑person sessions per month.
• This role is located in Toronto, Ontario.

We’re building a company where the work speaks for itself. We reward honesty, integrity, collaboration, a client‑first mindset, and genuine engineering craftsmanship. We move fast, communicate directly, and hold each other to a high standard because our customers depend on us. If you want a place where your contributions matter from day one and the quality bar is non‑negotiable, we’d love to hear from you.

Send your resume and a brief note on what excites you about this role. Bonus points if you can share a project where you shipped an LLM‑powered feature in production.