Systems architect / AI
Buget: -
HOURLY / PART_TIME
⭐ 4.97 (41)
United Kingdom
artificial-intelligence, machine-learning, artificial-neural-networks, cloud-computing, python
Preferred qualifications
- Experience: Intermediate
Hi,
We are looking for an exceptional engineer, or small development team, to build the technology infrastructure behind two interconnected businesses.
We want someone who ships quickly, keeps systems simple and knows when to buy, integrate or build. The immediate priority is a working MVP, not an over engineered platform.
Company A — Startup Incubator
Build a lightweight CRM and project management system covering founders, investors, mentors, partners, emails, relationships, projects, milestones and follow ups.
We are considering Attio as the core CRM, with email integration and AI used where genuinely useful.
The goal is simple: one place to understand our relationships, projects and what needs to happen next.
Company B — AI Talent & Human Intelligence Platform
We already have a large technical talent database across Supabase and GHL.
We want to turn this into an intelligent platform for finding, assessing and deploying exceptional people for both hiring and AI human training/evaluation work.
Examples:
“I need 200 competitive programmers to evaluate reasoning traces for three weeks.”
“I need 30 electrical engineers with power systems expertise.”
“Find me the best five ML engineers for this startup.”
The MVP should include:
* Semantic talent search and matching
* An ATS with strong LinkedIn integration / Apply Connect and always on talent acquisition
* AI assisted screening and assessment
* A structured talent/capability layer built around our existing data
* Simple workflows for deploying talent into hiring mandates or AI training/evaluation projects
We want to start simple, prove the workflows and build proprietary infrastructure only where it creates genuine advantage.
Who We Want
Strong full stack, systems architecture, APIs, Supabase/Postgres, AI/LLM and search/retrieval experience.
Familiarity with Mercor, Micro1 and similar AI talent/human data platforms is particularly important. We want applicants who can demonstrate that they understand how these companies actually work, what they do well and what could be built differently.
We particularly value people who bring creative approaches we have not considered, rather than simply implementing this brief literally.
In your application, tell us:
1. What would you build as the simplest working MVP?
2. What would you buy vs build?
3. What do Mercor/Micro1 do particularly well, and what would you do differently?
4. What would you add that we haven’t thought of?
The prize is building a system that knows who can perform valuable work better than anyone else does — and can activate those people on demand.
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