Founding AI Engineer
- Montreal, QC, Canada
Full-time
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Founding AI Engineer
Full-time·Montreal (Hybrid)
Kouvre is the AI agent for restaurants. Independent owners text it like an employee and it runs the business: promos, menus, prices, reviews, their website, all across UberEats, DoorDash, and Skip at once. No dashboards. We're already making restaurants money. One BOGO at a Montreal spot, launched by a single text, lifted UberEats revenue by 1,000% on a slow Tuesday.
As our Founding AI Engineer, you own the brain. You will partner closely with the Founding CTO to turn a plain-text message into the right action, building the reasoning, the agents, and the evals that make Kouvre feel less like software and more like a sharp employee who never drops the ball.
The Mission
Founding AI Engineer
Full-time·Montreal (Hybrid)
Kouvre is the AI agent for restaurants. Independent owners text it like an employee and it runs the business: promos, menus, prices, reviews, their website, all across UberEats, DoorDash, and Skip at once. No dashboards. We're already making restaurants money. One BOGO at a Montreal spot, launched by a single text, lifted UberEats revenue by 1,000% on a slow Tuesday.
As our Founding AI Engineer, you own the brain. You will partner closely with the Founding CTO to turn a plain-text message into the right action, building the reasoning, the agents, and the evals that make Kouvre feel less like software and more like a sharp employee who never drops the ball.
The Mission
- For the owner: Make Kouvre understand intent. When an owner texts "fill my slow Tuesday," Kouvre has to know what that means and do the right thing: the promo, the platform, the timing, without a brief.
- For the company: Make the agent trustworthy. The gap between a fun demo and a business owners depend on is everything you'll build: reliability, judgment, and knowing what not to do.
- The reasoning layer: The agent logic that maps a casual text to the correct, complete action across platforms, handling ambiguity the way a good employee would.
- The action agents: Generative agents that draft promo copy, build a campaign, reply to a review in the restaurant's voice, or turn a new dish into a social post.
- The eval pipeline: The harness that proves a change made the agent better, not just different. Your safeguard against shipping regressions into someone's livelihood.
- The judgment guardrails: Knowing when to act, when to confirm, and when to stay quiet. A 10/10 action or nothing.
- The continuous edge: Feedback loops that make the agent sharper with every restaurant it runs.
- Deep agent intuition: You've built real LLM systems (tool-use, orchestration, retrieval, evals) and you know their failure modes cold.
- Product instinct: You care about the owner's outcome, not model benchmarks. You think "did it do the right thing," not "was the output plausible."
- Ship-it capability: You take an idea from notebook to production and own the path to real users.
- Scrappy with ambiguity: Small datasets, messy real-world signals, and fuzzy goals energize you.
- Clear thinking: You can explain a precision, latency, and cost trade-off plainly and make the call.
- AI is the product. You're building the thing the company is, not a feature on a dashboard.
- Founding equity, and the rare chance to define an AI discipline from scratch, with a CTO who backs you.
- Live proof it works. An operator-led company that's already making restaurants money.
- Zero bureaucracy. Proof of work over process. The best agent is one an owner forgets is software.
- Montreal-based and hybrid. Work from home, and meet in person when it matters.
- Skip the resume and cover letter. We value proof of work over credentials. Show us something hard you've built and shipped, and the hunger to outbuild everyone else.
More about this job
Responsibilities
Build the AI reasoning layer and action agents that translate restaurant owners’ text messages into reliable actions across platforms, including promotions, campaigns, review replies, and social posts. Develop evaluation pipelines, judgment guardrails, and feedback loops to improve agent quality and prevent regressions.
Requirements
Candidates should have hands-on experience building real LLM systems involving tool use, orchestration, retrieval, and evaluations, and understand their failure modes. They should be able to take ideas from prototype to production, prioritize restaurant owners’ outcomes, work effectively with ambiguity, and clearly assess precision, latency, and cost trade-offs.
Skills
- LLM Systems
- AI Agent Development
- Tool Use
- Agent Orchestration
- Retrieval
- Evaluation Pipelines
- Reasoning Systems
- Generative AI
- Production Deployment
- Prompt and Intent Understanding
- Reliability Engineering
- Product Judgment
- Ambiguity Management
- Precision, Latency, and Cost Trade-Offs
- Feedback Loops
Benefits
- Founding Equity
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Engineering
- Food & Beverage
Keywords
- Artificial Intelligence
- LLM Systems
- AI Agents
- Tool Use
- Orchestration
- Retrieval
- Evaluation Pipeline
- Reasoning Layer
- Generative Agents
- Guardrails
- Feedback Loops
- Production Deployment
- Intent Understanding
- Promotional Campaigns
- Restaurant Technology
- Uber Eats
- DoorDash
- Skip
- Review Responses
- Social Media Content
- Reliability
- Precision
- Latency
- Cost Optimization