Founding AI Engineer
- Role
- AI / ML
- Experience
- Mid
- Employment
- Full-time
- Company size
- Startup
Open to CA only. Set where you work from to check your eligibility.
No BS summary
Founding AI engineer for a remote Canada role owning LLM agents, matching/retrieval, backend, and data. Needs 3+ years shipping production software, production LLM agent systems, embeddings-based retrieval/ranking/matching, and strong Python. Must overlap US Eastern time for a few hours.
Core skills
Required skills
Optional skills
We are hiring our Founding AI Engineer to own the agent layer of an AI-first fundraising platform: the conversational agents that run our warm outreach and investor relationships, and the matching engine behind them.
Paires is where founders come to raise capital. We pair them with the right investors from a large, engaged global investor network, then our agents run the warm outreach and manage the relationships that turn into meetings. It is a two-sided platform, a product for founders and a living network on the investor side, not one-way matching. We are live with paying clients, profitable and self-funded, and we run as a small, senior, flat team that ships fast.
THE ROLE
You own our core: the agent system that runs the product - agents that research investors, draft outreach that reads human, and carry investor conversations end to end - plus the matching engine that pairs founders with investors behind them. You build it, you scale it, and you run it. This is the most important surface in the product, and it is yours.
WHAT YOU WILL OWN
- The agent layer: one orchestrator routing work to specialist agents. Those agents research investors, draft outreach that reads human, and carry investor conversations end to end. Evals gate what they are allowed to do alone. This is where you start.
- The matching engine behind it: embeddings, ranking, scoring, and the feedback loop that makes matches sharper over time.
- The backend and data behind it all: Python, Postgres, Supabase, AWS, clean pipelines. The agent layer is built on the Claude Agent SDK and Pydantic AI.
- Shipping to production end to end, and the judgment to know what to build next as we scale.
YOU ARE A FIT IF YOU
- Have been one of the first engineers at a quick-growing company, running the show: you know what it takes to scale and deliver a product, not just manage it.
- Have at least 3 years of shipping production software behind you, and have taken a full app from zero to production and kept it running, end to end. This seat needs a whole-product builder, not only a model specialist.
- Have shipped LLM systems to production and have real examples you can walk us through, including an agent system that is more than a single prompt in a loop.
- Have built retrieval, ranking, or matching with embeddings in production.
- Write strong Python and reason clearly about data and systems.
- Design evals, because you care whether the output is actually good.
- Own outcomes end to end and move fast with AI tooling. You write the code yourself: this is a builder seat, not a management seat. There is no team to hand work to.
- Bonus: TypeScript in production, FastAPI, vector databases, fintech or fundraising.
WHAT WE OFFER
Fully remote and async. Your day overlaps with US Eastern time for a few hours - not full US hours. Meetings batch on Mondays and Thursdays, the rest is deep work. The best AI tooling, paid (Claude Code, Cursor, top models). Real ownership of the core product, with equity potential for the right person.
How to apply: hit apply, which takes you to our short application form. We read every application.
What you'll do
- Own the agent system that runs the product, including agents that research investors, draft outreach that reads human, and carry investor conversations end to end.
- Own the matching engine that pairs founders with investors.
- Build, scale, and run the core product surface.
- Own the agent layer with one orchestrator routing work to specialist agents.
- Build evals that gate what agents are allowed to do alone.
- Own the matching engine behind the agent layer, including embeddings, ranking, scoring, and the feedback loop that improves matches over time.
- Own the backend and data behind the product using Python, Postgres, Supabase, AWS, clean pipelines, Claude Agent SDK, and Pydantic AI.
- Ship to production end to end.
- Use judgment to decide what to build next as the product scales.
What they require
- Experience as one of the first engineers at a quick-growing company, running the show and knowing what it takes to scale and deliver a product.
- At least 3 years of shipping production software.
- Experience taking a full app from zero to production and keeping it running end to end.
- Whole-product builder, not only a model specialist.
- Production experience shipping LLM systems, with real examples to discuss.
- Experience shipping an agent system that is more than a single prompt in a loop.
- Experience building retrieval, ranking, or matching with embeddings in production.
- Strong Python skills.
- Clear reasoning about data and systems.
- Experience designing evals and caring whether output is actually good.
- Ability to own outcomes end to end and move fast with AI tooling.
- Writes code personally; this is a builder seat, not a management seat.
- No team to hand work to.
- Requires a few hours of overlap with US Eastern time.
- Preferred: fintech or fundraising experience.
Benefits
- Fully remote and async.
- Meetings batch on Mondays and Thursdays; the rest is deep work.
- Best paid AI tooling, including Claude Code, Cursor, and top models.
- Real ownership of the core product.
- Equity potential for the right person.
Paires is where founders come to raise capital. They pair founders with the right investors from a large, engaged global investor network, then their agents run warm outreach and manage relationships that turn into meetings.