foundermatcha
Founding Engineer | Fintech / AI Automation | Property Lending | UK/EU | Meaningful Equity
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About the Job
We’re helping an ambitious UK-based founder hire a Founding Engineer / future technical leader for an early-stage fintech building the technology infrastructure for faster property-backed bridge lending.
The founder has a background spanning economics, finance, accounting and venture investing, with significant experience investing in startups and operating within real estate debt.
The company is building technology designed to fundamentally improve how lenders assess, underwrite and execute property-backed bridge loans — automating key parts of the process from initial application through credit decision, legal completion and servicing.
The technology company is already established, and the priority is finding someone with strong technical ability who is excited by the problem and can turn the founder’s vision into a sophisticated, scalable product.
This is a highly hands-on founding role with significant scope to grow into a long-term technical leadership position.
The Product
The company is building an automation platform for lenders operating in the UK property-backed bridge lending market.
The technology will combine conventional software, integrations, AI-assisted workflows and, over time, machine learning to automate significant parts of the lending process.
This includes borrower and property due diligence, KYC and AML, valuation and title analysis, exit-risk assessment, credit decisions, legal processes and loan servicing.
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Over time, the platform could use historical loan data to predict outcomes such as completion delays, overruns and defaults.
You’ll
- Help design and build the core lending and underwriting platform
- Build rules, integrations and workflows across the lending process
- Develop AI systems for extracting and analysing information from applications and documents
- Automate borrower KYC, AML and document review processes
- Build technology for analysing valuation and title reports and identifying key risks
- Develop exit-risk scoring using borrower, property and market data
- Build AI-assisted credit papers and legal workflows
- Explore agentic workflows that can coordinate multiple steps and outside parties
- Help develop machine-learning models using historical loan data
- Work directly with the founder to turn ambitious product ideas into working technology
- Help define the company’s technical architecture and longer-term technology direction
You Are
- Strong in software engineering, with meaningful hands-on experience building real systems
- Comfortable working across APIs, integrations, data, automation and AI
- Interested in fintech, lending, credit, property or financial infrastructure
- Excited by problems involving automation, data and complex decision-making
- Entrepreneurial and excited by solving an ambitious technical problem from an early stage
- Comfortable operating with ambiguity and helping define the solution rather than waiting for a detailed specification
- Interested in AI, agentic systems and the potential of machine learning in financial decision-making
- Direct experience in fintech, lending, credit or real estate is useful but not essential
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Based in the UK or EU.
We Offer
- Meaningful equity and the opportunity to become a key early member of the company
- Significant ownership over the technical architecture, product and technology roadmap
- A genuine path toward senior technical leadership as the company grows
- The opportunity to build at the intersection of fintech, AI, property lending and financial infrastructure
- The chance to build technology designed to fundamentally improve the speed and efficiency of property-backed lending
About foundermatcha
foundermatcha connects ambitious startup founders with high-potential engineers, technical leaders and future co-founders.
Applicants complete a short AI-led interview covering technical background, motivations, working style and suitability for the opportunity.
“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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