Senior Backend Engineer - Do Health

Do Health; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Do Health, the first product within Voy’s health portfolio, is hiring a founding backend engineer. You’ll own major backend features, shape system architecture, and scale the blood testing infrastructure across the UK and beyond.

You’ll build AI personalization systems and improve reliability and observability while working directly with product, design and clinical teams. You’ll join a small, autonomous team with no management layer, delivering real features in months.

Qualifications

• 5–8 years backend experience and strong fundamentals.
• Startup or scale‑up experience with ownership of systems.
• Ability to discuss trade-offs, failures and improvements end-to-end.
• Proven track record shipping reliable systems and infrastructure.

Responsibilities

• Own major backend features end-to-end - design, build, ship, monitor, iterate.
• Shape architecture with the lead engineer and make real technical decisions.
• Scale blood testing infrastructure UK and internationally.
• Build production AI systems leveraging longitudinal health data at scale.
• Improve reliability, observability, and foundational systems as the product grows.
• Collaborate directly with product, design and clinical teams without handoffs.

Skills

Backend engineering

Architectural thinking

End-to-end ownership

Reliability observability

AI tools usage

TypeScript Node.js

Go Kotlin Python

Tools

Go

Kotlin

Python

Job description

The Opportunity

We're hiring a Founding Backend Engineer at Do Health - a mobile-first preventative health product co-founded by Dr Rangan Chatterjee, built as an independent startup inside Voy.

Voy is one of the UK's fastest-growing digital health companies (£300M+ revenue, doubling next year, ~2x YoY growth across men's health, metabolic health, menopause, hormonal health, TRT, dermatology and more). Do Health is its next chapter: the first product designed not to treat illness, but to prevent it.

The product combines regular blood tests, longitudinal health data, behaviour-change science and AI personalisation to help people make better lifestyle decisions over time. We already run AI systems in production at a scale very few UK companies match.

You'd join a 10-person team, partnering directly with our lead engineer on the backend. There's no layer of management between you and the work. What you ship in month one is what users get.

What You’ll Do

• Own major backend features end-to-end - design, build, ship, monitor, iterate. Not "contribute to" - own.
• Shape architecture alongside the lead. Real technical decisions, made by you, kept or changed based on what works.
• Scale our blood testing infrastructure across the UK and internationally as we expand.
• Build production AI systems - personalisation engines that act on longitudinal health data at scale.
• Improve reliability, observability, and the foundations that everything else depends on as the product grows.
• Work directly with product, design, and clinical teams. No tickets thrown over walls.

Who You Are

• 5–8 years of backend experience with strong fundamentals. We care more about depth than years.
• Experience at a startup or scale-up where you genuinely owned things. Architectural thinking.
• You can hold an end-to-end technical conversation about systems you've built - what trade-offs you made, what broke, what you'd do differently.
• A track record of shipping reliable systems. Not just features - the boring infrastructure that keeps them up.
• Comfort with judgement calls in ambiguous situations. Most decisions here don't have a clear right answer.
• Confident, responsible use of AI tools in your workflow. Not "vibe coding" - using them as a force multiplier where they help, ignoring them where they don't.

Nice-to-have, Not Required

• Strong TypeScript / Node.js experience (it's our primary stack, but we'll happily hire someone excellent in Go, Kotlin, Python or similar)
• Experience scaling systems to high user volumes
• Exposure to ML/AI systems in production
• Healthcare or regulated-industry experience