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AI Summary
Job Description
AI Builder (6-Month Contract)
Best10 | Remote | Reports to CEO, working alongside our Product Manager
About Best10
Best10 delivers online, highly personalised diet and lifestyle coaching through WhatsApp and our own platform. We work with medical insurers to solve their hardest problem: the 20% of members who drive the majority of health costs. Our coaches help those members change course before their health, and the cost curve, gets worse.
Our coaches each support around 200 clients. At that ratio, the difference between a good outcome and a missed one is knowing which client needs attention today. That is the problem you will be hired to solve.
The Role
We are looking for a builder, not an analyst. Someone who is excited about finding gaps in the business, validating them with data, and shipping working AI solutions in days, not sprints.
This is not a platform or strategy role. You will embed with our coaching team, understand what a day at 1:200 actually looks like, and build the AI workflows that let coaches spend their attention where it matters most. Everything you build must work for non-technical users and must survive after your contract ends.
You will work alongside our Product Manager, who owns the domain definitions (what "at risk" means, how coaches work) and who will run and extend these systems after your engagement. Your job is to build the engine. Theirs is to own it.
Your First 90 Days
We already know the first two problems. You will start here:
- Risk ranking (months 1-3). Build the layer that answers "of my 200 clients, which 20 need me most today?" Disengagement signals, missed check-ins, sentiment shifts, adherence patterns. Most of this signal lives in unstructured WhatsApp conversations and platform data. Turning that into a reliable daily priority list is the core of the job.
- Context briefings (months 3-5). When a client surfaces, the coach should have an instant briefing: goals, recent history, current risk, what has worked before. No scrolling through months of chat history.
Month 6 is handover: documentation, training, and making sure the systems run without you.
Key Responsibilities
- Build internal tools and coach-facing features on top of LLMs (Claude, OpenAI, open-source models)
- Turn unstructured conversational data (WhatsApp threads, coaching notes) into structured, reliable signal
- Design and maintain prompt chains, RAG pipelines, and agent workflows where they genuinely help
- Prototype rapidly, going from idea to working demo in days
- Evaluate model outputs, set up evals, and iterate on quality, with a focus on accuracy coaches can trust
- Wire AI into our existing systems (platform APIs, databases, WhatsApp, Slack)
- Own the full stack of what you ship: frontend, backend, model integration, deployment
- Sit with coaches regularly. Watch how they work. Build for their reality, not for a spec
What You Will Bring
- Demonstrable proof of using AI to build tools people actually use. We will ask you to show us, not tell us
- Proven experience shipping AI-powered products used by non-technical audiences
- Hands-on experience with LLM APIs (function calling, streaming, embeddings) and prompt engineering patterns
- Comfort working with messy, unstructured conversational data
- Strong product instinct: able to talk to a coach or founder, understand the real need, and build the right thing without a heavy spec
- Data-driven: willing to dig into the data, often building new reporting, to find root causes worth solving
- Fluency with agentic development tools (Claude Code, Cursor or similar) as part of how you work
- A builder's attitude toward handover: you take pride in systems that outlast you
- Fluent English
What Success Looks Like at Month 6
We will judge this contract on three things:
- The risk ranking and context briefing workflows are live and used by coaches weekly, without prompting
- Measurable improvement in time-to-intervention for clients who are disengaging or at risk
- Our Product Manager can run and extend the systems independently
If those three are true, there is a strong likelihood this becomes a longer-term role shaping how AI runs through the whole business.
What This Role Is Not
- Not a dashboard or BI role. Reporting may be a byproduct, never the product
- Not an ML research role. No model training from scratch, no fine-tuning for its own sake
- Not a strategy role. We need working software in front of coaches, fast
Additional Information
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