Job Description

We are hiring a Founding Engineer to work directly with the founder of an early-stage AI-native B2B SaaS startup building a specialist product for the institutional investment ecosystem.

This is a true 0→1 engineering role It is not suited to someone looking for a polished roadmap, a tightly defined specification, or a narrow engineering remit. We are looking for a deeply technical builder who is highly product-minded, comfortable with ambiguity, and motivated by turning complex, high-value customer problems into simple, reliable software.

The company is building for Limited Partners, Allocators, investment offices, endowments, foundations, OCIOs, family offices, fund-of-funds, and other institutional investment teams These organisations manage complex investment workflows involving manager research, due diligence, portfolio monitoring, investment memos, meeting notes, performance data, fund documents, LPAs, DDQs, reports, decks, emails, and other structured and unstructured information.

The product sits at the intersection of artificial intelligence, LLMs, document intelligence, workflow automation, structured and unstructured data, investment research workflows, and user-facing product design

This is not about adding a thin AI layer to an existing workflow. The challenge is to build an AI-native platform that sophisticated investment teams can genuinely trust, understand, audit, and rely on in their day-to-day work.

You will work closely with the founder to shape the product, make technical and product trade-offs in real time, and build the foundations of the company’s engineering capability.

What you’ll be doing

As Founding Engineer, you will help design, build, and ship the core product and technical platform from the earliest stages.

You will:

• Build core product and platform systems from scratch
• Work directly with the founder on product strategy, customer feedback, and product iteration
• Design and ship production AI features, not just prototypes or demos
• Build across the full stack, including frontend, backend, data, infrastructure, and AI workflows
• Design and implement LLM-powered workflows, RAG pipelines, agents, document-processing systems, retrieval systems, and evaluation loops
• Work with complex structured and unstructured data from documents, reports, investment materials, meeting notes, emails, and internal knowledge sources
• Build systems that help users extract, compare, summarise, query, and reason across investment-related information
• Own architecture decisions across application, data, infrastructure, security, and AI systems
• Think carefully about explainability, auditability, reliability, permissions, and data stewardship
• Translate ambiguous customer problems into simple, usable product experiences
• Move quickly while making pragmatic decisions about scalability, reliability, and maintainability
• Help define engineering standards, technical direction, and future hiring foundations as the company grows

Requirements

What we’re looking for

We are looking for someone with strong hands-on engineering ability and clear evidence of building products in fast-moving, early-stage environments.

You should bring:

• Strong software engineering experience across the full stack
• Clear 0→1 product-building experience, ideally in an early-stage startup
• Hands-on experience building AI-native products or production-grade AI features
• Working depth with areas such as LLMs, RAG, agents, document pipelines, evals, workflow automation, AI application architecture, and data-heavy products
• Experience building customer-facing products, not just internal tools, research projects, or prototypes
• Strong product judgement and the ability to make sensible trade-offs between speed, quality, and complexity
• An appreciation for trust, explainability, auditability, and reliability in AI systems
• High agency, low ego, and a willingness to work across whatever needs doing
• Comfort with ambiguity, incomplete information, and changing priorities
• A pragmatic engineering mindset focused on shipping useful product
• The ability to work closely and directly with a founder
• London-based or genuinely London-commutable for a hybrid working setup

Useful but not essential

We would be especially interested in people with experience in one or more of the following:

• AI-native B2B SaaS
• Fintech, investment technology, wealthtech, asset management technology, private markets technology, or institutional finance
• Document-heavy workflow automation
• Knowledge management, search, retrieval, or research platforms
• Secure data products for regulated or high-trust environments
• Products used by investment teams, analysts, researchers, operators, or professional services teams
• Complex enterprise or B2B workflows where accuracy, trust, and usability matter

You do not need to come from an investment background, but you should be interested in building for sophisticated professional users working with complex, high-value information.

Especially relevant backgrounds

This role may suit someone who has been a:

• Founding Engineer
• Technical Co-Founder
• Early engineer at an AI-native startup
• Senior Full Stack Engineer in a 0→1 startup environment
• AI Engineer or Product Engineer building production LLM applications
• Staff Engineer, Principal Engineer, or Senior Engineer with unusually strong startup and product-building experience
• Builder who has taken real ownership of product, architecture, and delivery in an early-stage company

Less relevant for this role

This role is unlikely to suit someone who is primarily a manager, architect, or advisor rather than a hands-on builder.

It is less likely to be a fit for:

• Pure engineering managers who are no longer hands-on
• Enterprise architects without recent startup or product-building speed
• AI-adjacent profiles without hands-on production experience
• Researchers who have not shipped customer-facing product
• Engineers who prefer a highly structured environment
• People looking for a narrow or clearly bounded remit
• Candidates who are uncomfortable building in a high-trust environment where accuracy, explainability, and user confidence matter

Benefits

Why join?

This is a chance to help define both the product and the company from the beginning.

You will have direct founder access, real ownership, and the opportunity to build an ambitious AI-native B2B platform from first principles. The role offers meaningful influence across product, technology, architecture, customer discovery, and the future engineering team.

For the right person, this is an opportunity to move beyond feature delivery and play a central role in building a product that changes how sophisticated investment teams work with complex information.