Data & AI platform engineer

Every year, hundreds of thousands of homeowners could move but don't, and homes that could sell never reach the market. The property market is slower and more closed than it should be. Homesearch is building the intelligence layer that gets it moving, connecting people, homes and agents through data and AI. Our vision is a fully connected, faster, more open property market.

• Build high-performance data and AI platforms behind our property technology services, spanning cloud infrastructure, data pipelines and production AI models.
• Work hands-on across the codebase, data pipelines, databases and cloud infrastructure to improve performance, scalability and reliability.
• Assess existing systems against real requirements, including performance, freshness, reliability, security and cost, and shape a practical plan for change.
• Modernise constrained legacy components incrementally, behind documented interfaces, without disrupting production.
• Improve how we acquire, ingest and serve data across feeds with different formats, freshness and reliability.
• Define canonical data models, shared identifiers and data contracts for the entities everything depends on: properties, addresses, listings, agents.
• Make large volumes of property assets, including images and floorplans, usable by our products and AI workloads.
• Build automated testing, deployment, observability, recovery and rollback into the platform.
• Create reusable components, templates and documented patterns so other engineers can work independently and safely.
• Share what you know through documentation, code review and hands-on work with our data, software and AI/ML engineers.
• Work closely with data scientists, product teams and senior leaders to translate business priorities into high-performance data pipelines and platform capabilities that deliver measurable value.

• You write, test, debug and explain production code, in Python, Java, Go, Scala, C#, TypeScript or similar, and your SQL and relational modelling are strong. You stay accountable for code you built with AI assistance.
• You've built and run modern data platforms: ingestion, transformation, orchestration, batch or streaming, and data serving, with a real grasp of operational databases, object storage, lakehouses and data contracts.
• You have deep production experience on at least one major public cloud (AWS, Azure or GCP), using Infrastructure as Code, CI/CD, automated testing, containers or serverless.
• You've modernised legacy systems incrementally, made architecture decisions you can defend with evidence, and built patterns that cut manual work and reduce reliance on any one person.
• You own production reliability: monitoring, alerting, incident investigation, recovery, performance and cloud cost.
• You've handled security, governance and data quality properly: access management, secrets, encryption, audit logging, lineage and cataloguing.
• You've supported data scientists and ML engineers, and you're comfortable with large datasets.
• You use AI-assisted engineering tools where they improve development, testing, documentation or troubleshooting, while remaining accountable for the quality, security and correctness of what you ship.
• You're collaborative and you listen. You respect what people already know about the systems and the domain.
• You're open to changing your mind when the evidence changes, and open to learning things you haven't done before. We rate this above years of experience.
• You take initiative, hold a high bar, and think architecturally rather than only executing tasks.
• You've worked at real data volume, somewhere that had to scale, and you're comfortable when priorities and constraints move.
• Будет плюсом: Building or running web-scraping and data-acquisition systems; Experience with PostgreSQL, MySQL or PHP based services; Supporting data platforms used by both live products and AI/ML workloads; Property, listing or other entity-resolution data; Search and indexing: Elasticsearch, OpenSearch or similar; LLMs, RAG, AI agents and the major AI application frameworks

• Competitive salary, plus a performance bonus and share options, so you share in the upside you create.
• 25 days holiday plus bank holidays.
• A MacBook to work on.
• An office with a free on-site gym, free yoga and gym classes, sauna and regular events.
• Hybrid working, 2 to 3 days a week at our office in London Victoria.
• The chance to own the data platform a whole company is built on, at a fast-growing PropTech at a real turning point.