Staff Full Stack Engineer

STAFF FULL STACK ENGINEER We’re a VC-backed stealth-mode company building behavioural AI solutions for the retail industry. Our platform is designed from the ground up — no legacy, no patchwork systems — just a clean slate and a clear vision. Our mission is to bring the intelligence of modern machine learning directly to the in-store shopping experience. We are taking an almighty swing of the bat; it is difficult, full of risk, and exactly why we are here. THE ROLE As a Staff Full Stack Engineer, you’ll work at the intersection of Product, ML, and Engineering to design and build the retail stack of the future; imagine AI driven content delivery on autonomous edge devices on an IoT network, combined with the backend infrastructure of a cutting edge adTech platform. This isn't a staff role where you "work across the stack"— you'll be an integral part of defining the stack. WHAT YOU WILL OWN - System Architecture: Design and lead the implementation of distributed, event-driven services that bridge the gap between cloud intelligence and edge devices. - Technical Strategy: Set the standards for service boundaries, data ownership, and system observability to ensure we scale seamlessly from 1 to 1,000+ locations. - AI Integration: Architect the orchestration layer for LLM-driven agentic workflows, moving beyond simple API calls to deeply integrated, autonomous system behaviors. - Mentorship & Culture: Continuously raise the bar for engineering excellence. Conduct deep design reviews, mentor mid-level engineers, and champion a culture of "building with AI" and the use of autonomous development agents to accelerate our velocity. ESSENTIAL QUALIFICATIONS - Track Record: 8+ years of experience, with recent years spent in a Staff, Lead, or Principal capacity at a high-growth startup or a sophisticated scale-up. - Full-Stack Mastery: Expert-level proficiency in modern backends (Python, Go, or Java) and high-performance frontends (React/TypeScript). - Distributed Systems: Experience designing and operating event-driven architectures at scale (e.g., Kafka, Pulsar, or MQTT). - Real-time Protocols: Mastery of async real-time, bi-directional communication protocols and patterns whether that's (WebSockets, gRPC, SSE, MQ) for low-latency data flows. - The "AI-First" Mindset: You don't just use AI tools; you have optimised your entire workflow around and can teach others to do the same. NICE TO HAVE - Edge & IoT: Experience with "Cloud-to-Edge" orchestration and managing state across geographically distributed systems. - Containerised Workloads: High comfort level with Kubernetes and container orchestration in a CI/CD-heavy environment. - Domain Expertise: Prior exposure to the complexities of large scale retailTech, adTech, or marTech platforms.