Mid Level Full Stack Engineer (Fast growing startup)

Stairpay; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Gym in the office

Work from anywhere 2 weeks/year

Latest equipment and AI tooling budget

25 days holiday + bank holidays

Generous stock options

Remote 1–2 days per week

Monthly team socials

Job summary

Stairpay is transforming affordable housing infrastructure in the UK. We’re looking for a hands-on full‑stack engineer who can own features end-to-end, from concept through deployment, coordinating AI agents while ensuring security, correctness and robust observability.

You’ll work across frontend, backend and database layers, shaping product direction and collaborating with housing associations to deliver real value.

Qualifications

• Strong TypeScript
• Modern React & Next.js
• Databases & APIs: SQL schema design, query optimisation, API design
• Cloud-native: AWS (or GCP/Azure)
• You work with AI and verify it; you direct agents
• Product-first mindset; think in outcomes, not just tech
• Nice to have: accountability, testing/observability, autonomous collaboration
• Client-facing confidence; fintech or property domain exposure helpful

Responsibilities

• Own features end-to-end from concept to deployment
• Direct AI agents, ensure security, correctness and guardrails
• Ship full-stack features to real users and fix issues
• Collaborate with housing associations and iterate on feedback
• Design tests and observability for safe deployments
• Shape product direction by questioning rationale and outcomes

Skills

Full-stack development

TypeScript

React

Next.js

Cloud services

SQL

APIs

AI tooling

Testing & observability

Collaboration

Tools

AWS

GCP/Azure

PostgreSQL

REST APIs

Job description

• The market - real estate is the largest asset class in the world, and a home is the most important asset most people will ever own. Stairpay is transforming the infrastructure that runs affordable housing in the UK and beyond, bringing automation and efficiency to a sector that has had very little of either, and making sure residents feel the benefit first
• The platform - it manages the purchasing journey, uses AI for document ingestion and regulatory checks, gives residents an app through which they manage their home, and provides the financial layer for large institutional landlords collecting millions in rent every month. Shared ownership is where we started and where we're strongest: the hardest tenure, and the one the incumbents handle worst
• The domain - statutory clocks, lease terms that differ per property, money maths where being 1% out is a regulatory problem. That's the moat, and it's why the work stays interesting
• How we build it - a platform that notices a problem, fixes it, proves the fix, ships it, and rolls it back if it's wrong. Money movement, authentication and destructive data migrations stay under human approval permanently - in our market that s a feature we sell, not a limitation we admit
• Where the humans sit - as the floor rises, we climb with it: deciding what's worth building, architecture, taste and UX judgement, customer understanding, and designing the evals and guardrails that define what "correct" means. Engineers here work at the frontier, always at the highest layer automation can t yet reach
• Own features end-to-end - concept → design → implementation → deployment → iteration. Ship regularly and confidently to customers who are using this every day
• Direct the machine, not just the keyboard - orchestrate AI agents across implementation, review and verification. Bring the fundamentals to bear on what comes back: security, correctness, error handling, UX
• Help build the harness that makes autonomy safe - tests, contracts, data invariants, evals, environments. Code is getting cheap to produce; the thing that defines correct is what we re really building, and it s what earns each class of change the right to travel further on its own. You ll help shape how we do it
• Raise the floor, then climb - every change should leave the platform easier for AI to work on: typed, tested, documented, conventional. As that compounds, the work you spend your time on moves up a level. Expect the job to look different in twelve months
• Work directly with clients - join calls with housing associations, watch real users hit real workflows, demo what you ve built and iterate on what you hear
• Shape the product - bring ideas, push back when there s a better way, think in outcomes rather than outputs

• Gym in the office
• Work from anywhere for 2 weeks a year (July, August, December)
• Latest equipment, and the AI tooling budget to go with it
• 25 days holiday plus bank holidays
• Generous stock options
• Work remote 1-2 days a week
• Monthly team socials

AI raises the floor. We raise the ceiling - that s our engineering vision. The floor is everything that happens without a person doing it by hand: implementing, verifying, reviewing, deploying, correcting, rolling back, around the clock. The ceiling is what s possible, and raising it is our responsibilityYou re the director, not a rubber stamp - this isn t a job where you type code all day, and it isn t a job where you wave through whatever a model produced. You decide what gets built and why, you direct the tooling that builds it, and you own whether it s right

Full-stack, shipped in production - you re taken complete features across frontend, backend and database into the hands of real users, and stayed to fix what brokeStrong TypeScript - comfortable with advanced patterns; you write type-safe code because it makes the system easier for the next person (and the next agent) to change safelyModern React & Next.js - you understand rendering strategies, data fetching and state management, and know when each is the right callDatabases & APIs - SQL schema design, query optimisation, sensible API design. You can spot an N+1 and know what to do about itCloud-native - you re deployed and operated on AWS (or GCP/Azure), and you re comfortable with managed services and serverlessYou work with AI, and you verify it - you direct agents on real work rather than autocompleting, and more importantly you catch where they r subtly wrong. Knowing where you don t trust it is the skill we re hiring for. You don t need to have built agent tooling before - you need to want toYou want to build the tooling, not just use it - how software gets built is being reinvented right now, and there s no playbook for it. We re designing the AI infrastructure this company runs on, and we want someone who d rather invent our version of it than wait for someone else sProduct-first - you ask "why are we building this?" before "what should we build it with"Nice to have:Accountable - you take responsibility for outcomes, follow through on what you commit to, and proactively unblock yourself. You ll be joining a small team who are keenly motivated to improve our systems and our output every dayTesting and observability as instinct - meaningful tests, visible failure paths. On our platform the tests aren t a chore; they s what lets a change ship without a human watching itAutonomous collaboration - you work independently, seek input on the big calls, and help teammates who are stuckClient-facing confidence - you can explain a technical decision to a housing association operations lead and enjoy doing itFintech or property domain exposure - useful, not required. What matters is caring that the money maths is exactly right