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About us
We're building the AI that makes healthcare make sense. Our platform combines real-time conversational AI, medically-validated content, telehealth, and e-commerce into one experience — so people get trustworthy medical guidance the moment they need it, not after a three-week wait for an appointment.
We're small, fast-moving, and ambitious. Every person on the team has real ownership over what we build — there's no "wait your turn" here. If you're early in your career and want your code, your decisions, and your ideas to actually matter from day one, keep reading.
The role
We're looking for a Data Engineer to build and own the data backbone of our AI platform. This isn't a "maintain someone else's system" role - you'll be the person who creates it. You'll turn millions of raw conversations and data points into the clean, structured, secure data that help decide the direction of the product.
You'll work directly with our CTO and Chief AI Officer.
What you'll actually be doing
- Build the pipes. Design and ship Python-based ETL/ELT pipelines that turn raw user and chat data into something usable - fast, reliable, and built to scale as we grow.
- Make sense of the mess. Take unstructured conversational transcripts and search queries and engineer ways to parse, tag, and extract real insight from them.
- Connect us to the world. Build and maintain integrations with external partners - including US online pharmacy platforms and healthcare services.
- Keep it clean and compliant. Own data integrity and privacy across our stack, keeping us aligned with GDPR, MHRA, and FDA standards (we'll teach you the healthcare-specific parts - you bring the engineering rigor).
- Give the team visibility. Set up dashboards, automated reporting, and monitoring so the wider team can actually see what's happening in the product.
- Leave things better than you found them. Refactor what needs refactoring, kill technical debt, and keep our systems fast and dependable.
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What we're looking for
We care far more about how you think and build than a box-ticking CV. That said, here's what will set you up to succeed:
- Strong Python fundamentals - you write clean, production-minded code and are comfortable in a shared Git workflow.
- Some real-world data pipeline experience - internships, side projects, or early roles building ingestion pipelines, REST API integrations, or working with high-volume data all count.
- Comfort with unstructured data - text, NLP outputs, or an interest in vector/graph databases (we use these for our AI models).
- Solid SQL and database knowledge - you understand relational design (PostgreSQL) and are curious about modern cloud data stores.
- A builder's mindset - you'd rather ship something and improve it than wait for the "perfect" spec. You're comfortable moving fast without breaking things that matter (like people's health data).
Get help with your application
Your very own career expert that helps elevate your application to the next level.
This role is not about years of experience, it's about ownership.
If you're a recent graduate who's shipped real projects (at university/internships/on your own) and you're ready to step up, we want to hear from you.
Bonus points if you have
- Any exposure to healthcare, health tech, or regulated data environments (GDPR, HIPAA, MHRA, FDA)
- Interest or experience with graph databases (e.g. Neo4j) or vector databases for AI/LLM applications
- Experience working with LLM conversational logs or chat-based products
- Familiarity with data tools like Metabase, Power BI, or Tableau
Why join us
- Ownership You'll build systems that directly power a healthcare AI product used by real people - not busywork, not shadow projects.
- Direct access to leadership Work shoulder-to-shoulder with our co-founders and execs. Your ideas get heard, not filtered through five layers of management.
- Flexibility that respects your life. Remote-first, with hubs in London and Dubai if you want in-person options.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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