Full Stack Engineer - AI Systems

Our client is an AI-native productivity startup on a mission to bring intelligence to everyday work (conversations, errands, organising and workflows) with minimal prompting. Their first product reimagines email, moving users from reading and writing messages themselves to reviewing and approving AI-completed work, with the goal of cutting average daily email time from around four hours to just thirty minutes. The business is backed by an initial $100m investment from a profitable, internationally established parent company, and is building toward a much bigger vision: a single AI application that reduces reliance on inboxes and chat tools altogether, with agents able to plan, act, and coordinate with each other on a user's behalf The Role They're hiring a Full Stack Engineer (AI Systems) to build the product layer that turns these capabilities into usable, production-grade workflows. Designing how agents operate, fail, recover, and deliver consistent value to users. What you'll do: Build end-to-end product features across frontend, backend, and AI integrationsDesign agent workflows that handle planning, tool use, failure, and recovery across multiple stepsIntegrate LLMs, memory, and external tools into systems that behave reliably under real-world conditionsDesign real-time AI interactions with streaming, partial results, and tight latency constraintsImprove system reliability, observability, and fallback mechanismsCollaborate closely with ML, backend, and product teams to ship features end-to-endIterate continuously based on real usage and failure modes What you'll own: AI-native product features that move beyond chat into persistent, goal-driven workflowsAgent workflows that reliably complete multi-step tasks across tools and sessionsLatency and responsiveness improvements to AI interactions, without sacrificing output qualityRobust fallback and recovery mechanisms for LLM and tool failures in productionPatterns and abstractions for integrating LLMs, memory, and external tools into scalable systems What They're Looking For Strong full-stack engineering experience (frontend + backend)Solid understanding of system design and API architectureExperience working with LLMs, RAG systems, or AI-powered applicationsAbility to handle ambiguity and make pragmatic engineering decisionsStrong ownership — able to take features from idea to productionComfort working in a fast-moving environment with evolving requirements Tech Stack Next.js · Python · Node.js · PyTorch · OpenAI / Anthropic / open-source LLMs · SQL & NoSQL · Kubernetes · Docker The Team A small, high-talent-density, hands-on team that makes decisions collectively and moves fast, balancing shipping high-quality work with learning as they go. This role requires bringing structure, exercising judgement, and executing independently. Package Competitive base and equity Interview Process If there's a fit, expect 3 interviews (no more than 4), conducted virtually and/or onsite, evaluated by the technical team.