Chief Software Architect

VP of Engineering – AI / Property Technology (London)

Company Overview

A rapidly growing, venture-backed start-up is building an AI-first platform that automates complex workflows within the property management sector. The business develops multi-agent, AI-driven systems that interact across chat, email, and voice channels to streamline communication, scheduling, and operational efficiency for property professionals.

Role Overview

The company is seeking a hands-on VP of Engineering to lead its technical function and drive the evolution of its core platform. This individual will oversee a multidisciplinary team covering AI, backend, frontend, DevOps, and QA , taking responsibility for system architecture, delivery, and scalability as the company transitions from start-up to growth phase.

Key Responsibilities

• Lead and scale a high-performing engineering team (currently 10–12 engineers across AI, backend, frontend, DevOps, and QA).
• Define and deliver the company’s long-term technical roadmap in close collaboration with the CEO and Product leadership.
• Stay approximately 70% hands-on — reviewing code, contributing to architecture, and supporting delivery on key technical initiatives.
• Establish engineering best practices across performance, reliability, and security.
• Oversee the design and implementation of AI-driven systems — including multi-agent orchestration, LLM integration, and data pipelines (LangChain, LangSmith, vector databases).
• Drive continuous improvement in CI/CD, cloud infrastructure, and deployment processes (Docker, Kubernetes, AWS).
• Mentor engineers, recruit top talent, and help shape a strong engineering culture built on accountability and innovation.

Requirements

• Proven experience leading and scaling engineering teams within start-ups or high-growth environments.
• 8+ years’ hands-on software development experience (Python preferred; additional exposure to JavaScript/TypeScript or Go beneficial).
• Strong background in AI systems, cloud-native architectures, and modern ML tooling (LangChain, OpenAI API, vector stores, RAG pipelines).
• Experience designing distributed, high-availability platforms deployed on AWS or similar cloud environments.
• Excellent communication and stakeholder management skills, with the ability to translate technical direction into business outcomes.
• Previous exposure to the property, SaaS, or workflow automation space is advantageous.

Summary

A rare opportunity for a technically strong, execution-focused engineering leader to shape and scale a next-generation AI automation platform from the ground up — with full ownership of the engineering strategy, team, and architecture.