Job Specifications
Company: Early-stage funded tech startup
What we need: Founding AI engineer
Type: Fractional to full-time
Location: Remote (UK preferred)
Why You'd Care
We're building something real for a customer group that's genuinely underserved. Not solving a nice-to-have problem, but something people actually want. We've got runway, we're funded, and we're not in survival mode. You'd be part of the technical direction, not inherit it.
What We're Building
A system that combines computer vision, natural language processing, and semantic search to solve a real problem in the healthcare industry. You'd architect the whole thing from scratch. Not just optimising models, but designing how all the pieces talk to each other, how we serve it at scale, how we know when it's working.
We're thinking about safety from day one because we must. In this space, you can't just ship and hope. You'd be defining what good looks like and building the systems to measure it.
Who We Need
10+ years experience shipping software. Five of those in production ML systems (actual deployed releases, not research). Two years at an early-stage startup where things changed and you had to figure it out.
Technical essentials:
• Python at an expert level
• Five years AWS hands-on (SageMaker, Lambda, ECS, you know when to use each)
• Built computer vision systems (object detection, image classification)
• Built retrieval systems with embeddings (Weaviate, Pinecone, Faiss)
• NLP and document understanding (parsing, OCR, transformers)
• MLOps fundamentals (Docker, CI/CD, model versioning, feature stores)
• You understand batch vs real-time inference and tradeoffs
The stuff that matters:
• You've shipped under pressure with incomplete info and it doesn't scare you
• You raise concerns about safety and data quality without needing permission
• You mentor people because you care about team quality
• You genuinely think about responsible AI and edge cases
• You'd rather ship something that works than spend months perfecting it
Nice additions:
• Healthcare or regulated industry experience
• Built products for underserved demographics
• Managed engineers before
• Supply chain or product information systems
What You'd Actually Do
Build the core AI system, architecture, model selection, inference optimisation, deployment. Get AWS infrastructure right so it scales and doesn't break. Work with the CTO on safety frameworks and evaluation. Set patterns that the next AI engineers follow. Help interview and onboard people as we build the team.
Basically: own the technical direction with input from the CTO. You're not reporting every decision up the chain, you're making calls and shipping things.
Why We're Different
You're not fixing someone else's mess. You're architecting from close to zero. Your technical decisions stick around.
We've thought about responsible AI. It's not a box we'll tick later, it's how we think. You'd be establishing practices that become industry-standard as we scale.
The company has runway. We're not in permanent fundraising mode. You can actually think long-term.
Fractional with a clear path. Three clear stages: trial, scoped project, then full engagement. If it works, and the signals are good, you move to full-time.
The Honest Details
Compensation:
• Fractional rate: £700-900 per day
• Equivalent full-time salary range: £122,000-£184,000 per annum
• Full-time package (salary, equity, benefits) gets discussed during offer conversations
Timeline: We want someone starting soon. The entire process should move quickly, from initial chat through to decision.
The Recruitment Process
Three-Day Trial
Candidates get hands-on with our prototype and help us chart a development plan. Over these three days, you'll put together initial system diagrams and frameworks, working closely with our DevOps team on the AI Ops side. This is where we see how you think and how you collaborate, no pressure, just real work.
Three-Week Project
If things click during the trial, we'll extend you to a three-week engagement to tackle a scoped project. This gives us both a clearer picture of working together at a slightly larger scale and proves out whether the technical direction is sound.
Three-Month Contract
Assuming all goes well, we'll bring you on for a three-month contract to work on the larger AI roadmap. This is where you're really embedded with the team, setting architecture patterns, and building the foundation that scales as we grow.
The Initial Interview
Round 1 (30 min): Just a chat. Background, motivation, what you're looking for. You ask questions too. Mutual fit assessment.
Round 2 (90 min): Talk about projects you've shipped. What did you build? What tradeoffs did you make? We sketch out architecture, not whiteboard performance, just how you think.
Round 3 (60 min): CTO conversation. Technical vision, safety, what early-stage really means. This is where we figure out if we'll actually work well together.
Hon
About the Company
From helping leaders unblock strategic opportunities to creating transformational product and technology experiences at scale, Rascal exists to grow your impact, joyfully. And rapidly, too.
We believe in positive disruption, and that solving meaningful problems requires continually challenging the status quo.
That means we always get to the core of what matters - joining you from "what if we..." to seeing your lasting positive change out in the world. Whatever route best gets you there. Ready to help you change the world...
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