Paires — a live, profitable, self-funded AI-first fundraising platform where founders come to raise capital — is hiring its Founding AI Engineer to own the agent layer of the product: the conversational agents that run warm outreach and investor relationships, and the matching engine behind them. This is the most important engineering seat at Paires — a builder role, not a management role — offering a fully remote, async-first position with compensation ranging from CA$230,000 to CA$370,000 plus equity potential, the best AI tooling available (Claude Code, Cursor, top models), and direct ownership of the core product.
About Paires — Live, Profitable, Self-Funded
Product: AI-first fundraising platform — pairing founders with the right investors from a large, engaged global investor network through AI agent-driven warm outreach
Status: Live with paying clients, profitable, and self-funded — a small, senior, flat team that ships fast
Tech Stack: Claude Agent SDK, Pydantic AI, Python, Postgres, Supabase, AWS — agents built on Anthropic’s most capable frameworks
Work Style: Fully remote and async-first — meetings batched on Mondays and Thursdays, the rest is deep focused engineering work
Why This Founding AI Engineer Role Stands Out
CA$230K–CA$370K Compensation: One of the highest-paying founding AI engineer roles available to remote UAE-based engineers in 2026 — plus equity potential
Full Core Product Ownership: The agent system and matching engine are the heart of Paires — this seat owns both, end to end
Best AI Tooling Paid: Claude Code, Cursor, and top models — all provided and paid for, with no cost to the engineer
Profitable Startup, Not Pre-Revenue: Join a live, paying, self-funded product — real traction, real customers, real stakes, no runway anxiety
Position Overview
The Founding AI Engineer at Paires owns the agent layer of the product — an orchestrator routing work to specialist AI agents that research investors, draft outreach that reads human, and carry investor conversations end to end, all gated by evals that determine what agents can do autonomously — and the matching engine behind it, including embeddings, ranking, scoring, and the feedback loop that makes investor-founder matches sharper over time. The role also owns the backend and data infrastructure — Python, Postgres, Supabase, and AWS — and ships to production end to end. This is a whole-product builder seat. There is no team to hand work to.
Why This Role Matters: As Founding AI Engineer at Paires, you build the AI system that determines whether founders find the right investors — the agent layer that researches investor profiles, drafts outreach messages that read like a human wrote them, carries investor conversations end to end, and learns from every match to become more accurate over time. On a small, senior, flat team that ships fast, your engineering decisions are Paires’ product decisions. Your agent architecture is the product. Your matching engine is the value. This is founding-level AI engineering with real commercial consequences and exceptional financial upside.
What You Will Own
The Agent Layer — Orchestration & Specialist Agents
- Build and maintain the agent orchestrator routing work to specialist AI agents — agents that research investors, draft warm outreach that reads human, and carry investor conversations end to end
- Design and implement evaluation frameworks (evals) that gate what agents are allowed to do autonomously — ensuring quality, safety, and business-appropriate decision boundaries
- Scale the agent layer as Paires grows — making architectural decisions that allow the system to handle increasing volume and complexity without degrading quality
The Matching Engine — Embeddings, Ranking & Feedback Loops
- Build and maintain the matching engine that pairs founders with the right investors — using embeddings, ranking algorithms, and scoring models that improve with every data signal
- Design and implement the feedback loop that makes matches sharper over time — continuously improving signal quality and match accuracy from real-world outcomes
- Apply retrieval, ranking, and matching techniques with embeddings in production environments — not just research prototypes
Backend, Data Infrastructure & Production Shipping
- Own the backend and data pipeline behind it all — Python, Postgres, Supabase, and AWS — maintaining clean, reliable data infrastructure that the agent layer depends on
- Ship to production end to end — writing the code yourself, owning the deployment, and making real-time judgements about what to build next as Paires scales
- Maintain proficiency across the full stack — this is a builder seat with no team to hand work to; whole-product ownership is the expectation from day one
You Are a Fit If You
Essential Requirements
- 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 — including taking a full application from zero to production and keeping it running end to end
- Have shipped LLM systems to production with real examples you can walk 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 environments
- Write strong Python and reason clearly about data and systems architecture
- Design evals — because you care whether the agent output is actually good, not just plausible
- Own outcomes end to end, move fast with AI tooling, and write the code yourself — this is a builder seat, not a management seat
Bonus Qualifications
- TypeScript in production — a significant bonus for full-stack coverage
- FastAPI framework experience
- Vector database experience — Pinecone, Weaviate, Qdrant, or equivalent
- Fintech or fundraising domain experience
About Paires — Where Founders Come to Raise Capital
Paires is where founders come to raise capital. The platform pairs them with the right investors from a large, engaged global investor network, then AI 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. Paires is live with paying clients, profitable, and self-funded, run by a small, senior, flat team that ships fast and values whole-product builders over model specialists or junior-team managers. The Founding AI Engineer role is the most important engineering seat at Paires — and with compensation of CA$230,000–CA$370,000, equity potential, and full remote flexibility, it is one of the most compelling AI engineering opportunities available to UAE-based engineers in 2026.
Career Excellence: Own the agent layer and matching engine of a live, profitable AI fundraising platform — CA$230K–$370K + equity, fully remote from UAE.
Who Should Apply?
- Founding / Early-Stage AI Engineers: Who have been among the first engineers at a fast-growing company — owning the full product lifecycle, not just a feature lane
- LLM Agent System Builders: With production-deployed agent systems — multi-step, multi-agent orchestration, eval-gated — not just RAG prototypes or single-prompt loops
- Embeddings & Matching Engine Engineers: With production retrieval, ranking, scoring, and embedding-based matching systems — built and maintained in real commercial environments
- Python Full-Stack AI Engineers: Comfortable owning backend, data pipelines, and production deployment — FastAPI, Postgres, Supabase, AWS — alongside the AI/ML layer
- Remote UAE-Based Senior Engineers: With 3+ years of production software delivery, async-first work experience, and availability for US Eastern time overlap
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