Founding Engineer

Role. Founding Engineer (AI / Product) Location. remote, UK Type. Full time, early equity --- About PlannrAI PlannrAI helps land and planning teams in UK housebuilding go from a question to a decision-ready answer in minutes, using the information they already have, with clear evidence every time. We want to change how land and planning teams support the building of future communities. You will be a pioneer in how AI is used in this space. --- Why this role matters You will be the first full time engineer. You will: Turn workflows and prototypes from our consultants into a product that real land and planning teams can trust. Lay the core technical foundations for PlannrAI. Turn complex land and planning workflows into working AI agents and product features. Shape our engineering culture, delivery habits and quality bar from day one. This role is: Output focussed. You are measured on what ships and what land and planning teams adopt. Mission driven. You care that land and planning teams get better answers, faster, for real sites and communities. --- What you will do 1. Build and ship the core platform Own the technical roadmap with the founder. Decide what to build now vs later. Turn early scripts and PoCs into reliable services and APIs. Design clear data models around projects, sites, documents and questions. Set up CI, basic monitoring and alerting so we can ship fast without losing control. 2. Turn agent ideas into real workflows Work with our existing AI and data consultants to: Design and build automations & workflows that match real land and planning tasks. Choose and wire together tools for orchestration, RAG and function calling. Define how agents show evidence, uncertainty and gaps so land and planning teams can trust outputs. Run small experiments with different prompts, tools and flows, then keep what works. 3. Build strong data cleaners and pipelines Turn messy construction data into clean, usable inputs. PDFs, emails, planning portals, reports, GIS layers and checklists. Design “data cleaners” that standardise formats, detect missing fields and flag quality issues. Work with consultants to design extraction and parsing flows that are testable and repeatable. Keep a tight link between data quality and product behaviour so we know why an answer went wrong. 4. Product and feature development Work directly with land and planning teams and consultants to understand their real questions. Translate those workflows into small, testable product slices. Example. “Show all objections on this site and how we responded” as a single end to end feature. Pair with the founder on UX and copy, especially around evidence and risk. Ship features to pilot users, watch how they are used, improve them in short cycles. 5. Delivery, quality and culture Set and keep clear delivery goals for each fortnight, then ship. Write tests where failure would damage trust or waste time. Keep simple technical docs so others can join later without guesswork. Help hire the next engineers. Share what good looks like and protect standards. --- What you bring You do not need to tick every box. You should recognise yourself in most of these. Engineering skills Strong software engineering background. You have built and run production services in Python or TypeScript. Experience with LLM based products or ML systems in production. Comfortable with: Building RAG style systems over unstructured documents. Working with a major cloud platform such as AWS, Azure or GCP. Modern data stores. SQL and at least one vector store. You care about logging, observability and simple ways to debug live systems. AI and agents Hands on experience with at least one LLM framework or API. Example. OpenAI, Anthropic, Gemini. You have built agents or tool calling flows, not just chat demos. You understand trade offs between speed, cost, accuracy and safety, and can explain them in plain English. Product mindset You enjoy speaking with users and domain experts. You can turn a vague land or planning workflow into a very small, shippable slice. You are comfortable saying “no” or “not yet” to protect focus. You like to measure what you ship. Example. Time saved per question, number of questions answered per week. Accountability and delivery You have owned a project end to end before, from idea to live use. You are happy with clear targets around delivery and quality. You are open about risks and blockers early, and you propose a path forward. You care about ethics, governance and the impact of AI on land and planning teams, applicants and communities. --- Nice to have Experience in construction, land, planning, GIS or related fields. Past work in an early stage startup or as a first or second engineer. Experience with document parsing, OCR, or working with planning portals. Familiarity with AI governance, ISO 42001, or similar standards. --- Compensation Salary. Competitive and negotiable based on experience. Equity. Meaningful ownership as part of the founding team. You share in the upside if we change how land and planning teams support future communities.