Lead Architect - Agentic AI

JOB SUMMARY We’re looking for a hands-on senior engineer who has taken full architectural ownership of enterprise software, someone who designs and builds complete, standalone applications end-to-end, including the database layer, third-party integrations, and enterprise-grade security and governance controls, rather than someone who has mainly worked on top of an existing managed data or ML platform. Genuine, hands-on experience operating a live, production-scale AI system is essential, including responsibility for its reliability, monitoring, incident response, and ongoing improvement, rather than experience limited to early-stage prototyping. This is a hands-on leadership role: part lead architect, part product owner, part governance lead. You’ll own the product’s architecture from the ground up while also bringing hands-on experience training Small Language Models (SLMs) and directing a developer focused on that work. You’ll be the technical anchor for the product — setting direction, challenging the roadmap where needed, and ensuring the system is secure, reliable, and built to scale for enterprise customers. JOB RESPONSIBILITIES Take full ownership of the technical direction of the agentic AI product Architect and build the product end-to-end, including designing and directly owning the core database layer, rather than relying on a pre-built or managed data platform Build and own the integration layer connecting to third-party enterprise systems, including authentication protocols, webhooks, rate limiting, inconsistent vendor behaviour, and API versioning Own the event-driven architecture underpinning the platform’s core workflow and orchestration engine, including queues, workflow orchestration, and idempotency Implement enterprise-grade controls — role-based access control, single sign-on, audit logging, tamper-evident record-keeping, and self-hosted/on-premises deployment (Docker/Kubernetes), to meet the product’s data sovereignty requirements Embed application security into every layer of the architecture, from code to deployment Design the agentic system’s guardrails and safety constraints, manage inference-rate and latency trade-offs, and decide where to use deterministic, rule-based workflows versus AI-driven processes Take ownership of the operational reliability of the live system — monitoring, incident response, and ongoing improvement, not just feature delivery Establish and enforce governance operations — data handling, model behaviour, access controls, and change management Lead a small technical pod, including directing and reviewing the work of a developer focused on training the company’s Small Language Models Bring genuine business acumen to technical decisions — balancing customer needs, cost, and delivery timelines Manage requirements and delivery through Jira, maintain the codebase in GitHub, and coordinate UI build-out via Loveable Produce clear, thorough documentation for…