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We are hiring an Applied AI Engineer to own the conversation layer of an AI-first fundraising platform: the agents that handle every reply, carry conversations through to booked meetings, and look after every relationship across our warm outreach, our investor network, and investor relations. 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, live with paying clients, profitable and self-funded, built by a small, senior, flat team that ships fast. The role You own how Paires converses: every reply handled well and in time, booking, nurture, and the coaching experiences we are building on the same data. It starts as our reply and messaging system and grows into a core part of the product. You will also build broader applied-AI features across the platform. What this seat is not: a research seat. An internal knowledge bot or a RAG demo is not the bar. We want people whose systems hold real conversations with real people outside their team, day after day. Cold outreach from nothing is a different seat too - here the conversations already exist, and your agents carry them. What you will own Agents that read inbound messages and draft the right reply, fast, with a human in the loop. The messaging layer across our warm outreach, our warm investor network, and investor relations, not just one inbox. Conversational agents end to end: replies, booking, nurture, and support that reads human. The eval spine that gates quality: golden sets, judges, and the guardrails that hold as the conversations grow. Broader applied-AI features: classification, extraction, routing, summarization. You are a fit if you Ship conversational LLM systems to production with real users: reply handling, support, booking, or nurture agents. Inbound work counts fully here. Have built evals yourself: golden sets from scratch, judge criteria, ship or rollback decisions made on the numbers. Have integrated LLMs with email, CRM, or messaging systems. Think like an operator, and know the business goal behind the message. Are an engineer first. We run roughly 80/20 engineering to research. Move fast with AI tooling and own outcomes. Our stack: Python, Supabase, Pydantic AI, Claude Agent SDK, AWS. If you have shipped on any of it, lead with that. Bonus: email and CRM integrations, RevOps exposure, sales or IR experience. 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). How to apply: hit apply, which takes you to our short application form. We read every application. Compensation Range: CA$200K - CA$330K
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.