Data & AI Platform Engineer

Homesearch; Greater London; Hybrid; GBP 90,000 - 140,000; Full time

Benefits offered by this job

MacBook

On-site gym & wellness facilities

Hybrid work 2–3 days in London office

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Job summary

Homesearch is building the intelligence layer to connect people, homes and agents through data and AI. You’ll join a strong Data & AI team to scale our data and AI platform, handling billions of data points and images, driving reliable pipelines, and enabling AI models for estate agents across the UK.

This is a hands-on, hybrid role in London, with modern data stacks and production-grade systems. You’ll influence architecture, improve performance, and collaborate with data scientists and senior

Qualifications

• Proficient in Python, Java, Go, Scala, C#, TypeScript and SQL for production-grade data pipelines and AI workloads.
• Experience building and maintaining scalable data platforms with cloud infrastructure and IaC.
• Strong understanding of data models, data contracts and data governance for large datasets.

Responsibilities

• 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.
• Extra points for: 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.

Skills

Python

Java

Go

Scala

TypeScript

C#

SQL

Data pipelines

Cloud platforms

CI/CD

Containers

Serverless

PostgreSQL

MySQL

Elasticsearch

OpenSearch

AI/ML

Data contracts

Data governance

Security

Tools

AWS

Azure

GCP

Terraform

Kubernetes

OpenSearch

Elasticsearch

PostgreSQL

MySQL

Job description

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.

We're one of the UK's leading PropTech platforms for estate agents, helping them win more listings, understand their local market, and turn existing contacts into new instructions. Our products, including HAILO and ReContact, are picking up real momentum and fast becoming tools agents know and trust. We're a trusted partner to Reapit, Dezrez, Rex, MRI and other leading CRMs, and we're on our way to One Homesearch: a single, unified platform rather than a collection of tools.

About the Role

Each of our products runs on property data. Billions of structured data points across properties, addresses, listings, agents and market events, plus hundreds of millions of images, floorplans and other property assets. It arrives through multiple feeds and acquisition methods, each with different freshness, completeness and reliability, and it changes constantly. It serves both live customer products and our AI and ML workloads. That data platform is the company.

The hard part is making that trustworthy: resolving inconsistent records into reliable property, address, listing and agent entities, keeping it fresh as the market moves, and serving it economically to live products, search and production AI from one platform.

You'll join a strong team of engineers and data scientists to build and scale the next generation of Homesearch's data and AI platform. Working with large property datasets, you'll automate and improve data pipelines, strengthen our platform foundations, and build reliable, high-performance services. Your work will help the wider team ship safely and quickly, while enabling our data scientists to develop production-grade AI models that power products used by estate agents across the UK.

You'll sit in our Data & AI team, working alongside two data engineers and reporting to Dan Guo, our Head of AI and Data, who worked on AI, data and Copilot at Microsoft and led data at SwiftKey before joining us. You'll work with him closely on the architecture: challenging decisions, shaping them, and turning ambitious AI ideas into systems that hold up in production.

This is a hands-on role. You'll be in the code, the pipelines, the databases and the cloud infrastructure, and you'll have real say in what the platform becomes.

What You'll Do

• 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.

Extra points for:

• 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.

Our values run through everything we do. Remove Friction: make everything seamless. Stay Curious: ask, learn, improve. Own It: take the lead, own the result. Raise the Bar: think big, deliver value. We're high performers who care about the mission and each other. High standards, open communication, and no room for ego or politics.

• Competitive salary, plus a performance bonus and share options, so you share in the upside you create.
• 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.