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Cheerful Monster Limited, a London-based AI-focused software studio, seeks a senior product engineer to own client outcomes end-to-end from discovery to production.
You'll work in a small, mission-driven pod, collaborating directly with clients, designing systems in Elixir, Phoenix, and LiveView, and guiding architecture decisions while balancing risk and delivery speed. This role is based in Canary Wharf with some flexible work.
Cheerful Monster is a small, London-based AI digital studio that builds software for clients, mostly in healthcare. Small senior teams own the work end to end, from discovery to production, and use AI to remove the grind rather than cut corners. We intend to find the new layout of the software workshop in the AI era, and to publish what we learn, failures included, so plainly that others can follow. We are a responsible services provider rather than a body shop. We aim to punch well above our weight through honesty, craft and quality, and have fun along the way.
If you’re a senior engineer with strong fundamentals looking to retool for AI-native development — or already an AI-native developer looking for an environment designed around it — read on.
Cheerful Monster is a London-based development studio building software with a smile. We deliver world-class AI and software for clients.
We combine product thinking, technical strategy, and software delivery in one small, senior team. Rather than passing work down a chain of specialists, our engineers work directly with clients and own outcomes from discovery to production.
We’re hiring a senior engineer to deliver client work now and grow out our small engineering team. This is a full-time role, working primarily from our Canary Wharf office in London, but with some ability to flex.
You’ll work as a product engineer in a small, mission-driven pod, directly with clients, taking problems from early ambiguity through design, implementation, and deployment to production outcomes.
Our first projects will use Elixir, Phoenix, and LiveView. Experience of using this stack on at least one production system would be helpful.
Coding agents will be a core part of the normal development environment: exploring codebases, developing plans, implementing features, generating tests, reviewing changes, and investigating production faults.
You remain accountable for their output and whether it is fit to deploy. AI makes writing code cheap, but it cannot decide what should be built, understand the client’s situation, make sound architectural trade-offs, or establish that plausible-looking output is actually correct.
The initial environment centres on Elixir, Phoenix, LiveView, OTP, Ecto, Ash, and PostgreSQL, alongside testing, Git, CI/CD, cloud deployment, and observability tooling.
Experience in other languages is welcome but not required. Python is particularly useful, whether you’ve used it for services, data, automation, scientific computing, or AI integrations. Experience in another ecosystem is also valuable where it demonstrates real depth and an ability to move intelligently between technologies.
Experience with Oban, Broadway, distributed Elixir, data engineering, LLM integrations, regulated domains, consultancy, early-stage products, or coaching other engineers would all be useful. We don’t expect one person to bring all of them.