Product Engineer, REalyse

• Strong fullstack technical ability
• Clear product thinking
• High ownership and accountability
• Strong fullstack capability (required)
• You must be able to operate effectively across a significant portion of the stack:
• TypeScript & React (modern patterns, performance, state management)
• API design and integration (REST and/or GraphQL)
• Backend development (Golang)
• SQL and data modelling (PostgreSQL preferred)
• Experience working with production systems
• Take responsibility for problems and drive them to completion
• Are comfortable with ambiguity and can move forward without perfect specs
• Focus on outcomes, not activity
• Identify risks and raise them early
• Balance speed with engineering quality
• CI/CD pipeline design and ownership
• Experience working in startup or scale-up environments
• You think like an owner, not an implementer
• You care about building products, not just writing code
• You are proactive, not reactive
• You communicate clearly and challenge when needed
• You raise the standard of the team around you
• If you're an experienced fullstack engineer who wants to own systems, work on meaningful technical challenges, and help build AI-powered products, we’d love to hear from you

Desirable

• REalyse builds the data and intelligence layer for the UK property market
• Our platform processes large-scale geospatial, planning, and transactional datasets to power valuation models, portfolio monitoring tools, and AI-driven workflows used by property professionals across the country
• We combine modern frontend systems, high-performance backend services, and AI to solve complex real-world problems
• This is not a “ticket-driven” engineering role
• You will be responsible for owning and delivering product features and systems end-to-end – from idea through to production – across frontend, backend, and infrastructure
• Design, build, and ship features end-to-end across frontend, backend, and infrastructure
• Take ideas from concept → production with minimal hand-holding
• Ensure what you ship works in the real product, not just in isolation
• Translate product goals into technical solutions
• Make pragmatic trade-offs between speed, quality, and scalability
• Design solutions that are maintainable and evolve with the product
• Write clean, reliable, and scalable code across the stack
• Improve performance, observability, and reliability of existing systems
• Debug and fix issues in live environments
• Collaborate closely with product, data, and design
• Challenge requirements and improve solutions
• Think about user impact, not just implementation
• Use tools like Cursor, Copilot, and LLMs to accelerate delivery
• Build and integrate AI-powered features where appropriate
• Maintain engineering quality while moving fast
• Raise the quality bar across the codebase
• Mentor other engineers where needed
• Improve developer experience, tooling, and workflows
• Engineers own problems end-to-end
• We optimise for impact, not activity
• We use AI extensively in our workflows
• We favour pragmatic solutions over theoretical perfection
• We collaborate closely across engineering, data, and product
• By 3–6 months, you will:
• Have delivered multiple production features end-to-end, from ambiguous idea through to shipped product
• Operate with high ownership – proactively driving work forward with minimal oversight
• Make and influence technical decisions, not just implement them
• Work effectively across the stack (React, Golang, data layer) and debug issues in production
• Use AI tools to meaningfully accelerate delivery without compromising quality
• Raise the bar for the team through code quality, feedback, and improved ways of working

• We aim to move quickly and minimise unnecessary stages. The process typically includes:
• Initial screening call
• Technical interview
• Practical exercise
• Final interview