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.

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.

• 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.

• 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/Type Script ).

• 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 (Web Sockets, 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.

• 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 retail
  
  Tech, adTech, or marTech platforms.