Lead AI Engineer

Acorn Insurance is hiring a Lead AI Engineer. This is a senior individual contributor role responsible for the engineering practice, platform and infrastructure underpinning our AI Services function. You will help delivery on the AI strategy at Acorn, pushing our technical direction, platform decisions, and bringing strong software engineering discipline to how AI gets built.

The role spans the AI platform end to end: infrastructure, observability, governance, and the toolset that supports AI delivery across the business. You will work directly with the Head of AI Services on AI strategy and platform direction, with the Conversational AI workstream on integration work, and act as the technical escalation point for engineers across the AI function. The role is expected to set and uphold the engineering and governance standards that the AI function runs to.

• Job title: Lead AI Engineer
• Salary: up to £60,000 depending on experience
• Working hours: 37.5 hours per week, Monday to Friday
• Location: Liverpool City Centre on a hybrid working basis

• Help lead AI strategy at Acorn alongside the Head of AI Services: shape direction, roadmap and the engineering vision for the function.
• Own a substantial share of the AI platform infrastructure: Azure, AKS, Terraform, Helm, Azure Pipelines. Lead its evolution, reliability and operational health.
• Lead engineering practice across AI Services: code review, testing, source control hygiene, deployment patterns, observability.
• Set and uphold observability, performance and governance standards for AI solutions across the business: DPIAs, model documentation, audit trails, evaluation harnesses.
• Integrate APIs cleanly: REST and webhook patterns, OpenAPI, authentication, retry / backoff, contract testing.
• Partner with the Conversational AI workstream to integrate internal APIs with Chat and Voice tooling (Boost.ai, ElevenLabs, comparable platforms).
• Lead evaluation of new platforms, frameworks and AI tooling; drive adoption decisions for the function.
• Act as technical escalation point for AI engineers across the wider function.
• Run cross team forums to share patterns, new tooling and engineering practice.
• Lead expansion of AI capability into new business domains as the AI estate grows.
• Provide technical direction and mentorship to engineers across teams; raise the engineering bar.
• Operate within a regulated AI governance model: DPIAs, model documentation, observability, human in the loop where appropriate.

• Strong production engineering track record - software, AI or ML at scale, in environments where reliability matters. Real software development practice, not just AI tinkering.
• Working knowledge of LLM application patterns: RAG, structured extraction, evals, prompt and context engineering, agentic workflows.
• Comfort integrating APIs cleanly - REST / webhook, OpenAPI, authentication patterns, retry / backoff, contract testing. You understand how production integrations actually fall over.
• Conversational AI awareness - familiarity with Boost.ai, ElevenLabs or comparable voice / chat platforms, and how to wire them up to internal systems sensibly.
• DevOps fluency: Azure (essential), AKS, Helm, Terraform, Azure Pipelines strongly preferred. You should be comfortable across the whole stack rather than purely application layer.
• Track record of putting observability, governance and audit story in place at scale.
• Awareness of the constraints of regulated environments: data residency, auditability, ZDR, model risk - design with them in mind from the start.
• Track record of mentoring engineers across teams and shaping engineering culture.
• Comfortable making and defending architecture / tooling calls; comfortable being challenged.
• Senior enough to operate as a credible technical co owner of the AI platform alongside the Head of AI Services.

The technical seat in the AI function with the Group AI Team. You will support with owning the platform, set the bar for engineering practice, and shape how AI scales at Acorn across new domains and new use cases. Executive backing and a real mandate to do the engineering properly.