Artificial Intelligence Engineer

On behalf of a well-funded and rapidly growing early stage AI development company focused on the compliance space we are seeking an AI engineer who is excited by rapid experimentation and deep platform R&D.Role:Turn customer conversations into focused, working POCs on a short turnaround, then identify what should become a reusable platform capabilityDesign and ship multi-agent pipelines for document generation, compliance checking, and BQ (Bill of Quantities) verificationBuild the intelligence layer that brings deep domain and compliance knowledge into every workflow, rather than solving the same problem customer by customerBenchmark frontier models (GPT, Claude, Gemini) against domain-specific tasks; own the evaluation frameworkBuild retrieval, reasoning, and structured output layers — our documents need to be auditable, not just plausibleDevelop and maintain our internal skill library on the Mink platform — reusable AI agents deployable across client workflowsIntegrate CAD/drawing inputs with document output pipelines (cross-referencing drawings against BQ items, safety plans, method statements)Run bi-weekly research reviews — we stay at the frontier and implement what mattersWork with domain experts (QS, safety engineers, civil engineers) to encode deep compliance logic into AI workflows

Requirements

2+ years hands-on AI/ML engineering & 10+ years in software development.Strong in LLMs, RAG, multi-agent systems, and structured output design.Python-first, hands-on with LangGraph (or a comparable agent-orchestration framework) — you can build, debug, and extend a real graph.Agent instincts — you've built or extended an orchestration loop (tools, state, retries, human-in-the-loop), not just called a chat API.You experiment before you theorise — new models, new frameworks, you test them and report what's real.Startup instincts — you operate in ambiguity and ship without a perfect spec.Document understanding, OCR pipelines, or structured compliance logic — a real plus.Comfortable across the stack — happy in a Python and a TypeScript web app in the same week.