Staff AI Engineer

You will be one of the most impactful early hires in this next stage of AI expansion. You will join at a moment when the company is actively forming its approach to AI foundations: tooling decisions are being made, agentic patterns are being established, and the kernel of a centralised AI platform is being laid out. Your role is to govern the quality and coherence of those decisions before they crystallise. You will initially work across the AgentForce and Investigations & AI teams, holding the architectural bar on tooling evaluations, keeping the stack decision open and well-reasoned, and ensuring that internal agentic patterns being developed today are genuinely inheritable by customer-facing AI products of tomorrow. You will act as a strong advocate for AI adoption, technical best practices, and enablement across product, engineering, and development. This is a role for you if you are comfortable with ambiguity, energised by the challenge of making decisions that others will build on for years, and confident enough to hold a strong technical position without needing a team beneath you to do it.

Responsibilities

• Serve as the architectural conscience for early AI decisions, evaluating current tooling explorations against the requirements of production-scale customer-facing AI products and producing evidence-based recommendations
• Work consultatively with the Investigations & AI technical lead and AgentForce engineering to ensure agentic patterns, prompt architectures, and evaluation frameworks are designed with customer-facing scale and regulatory auditability in mind
• Hold the AI stack decision open responsibly by documenting trade-offs, establishing evaluation criteria, and preventing pragmatic local choices from defaulting the answer prematurely
• Define and uphold engineering standards for AI systems across the organisation including model observability and tracing, prompt versioning and registry, cost governance, evaluation harnesses, and agent reliability patterns
• Produce technical foundation documents presenting a coherent architectural position, decisions made and deferred, and an honest assessment of what the architecture can accomplish

Requirements

• Made production AI architectural decisions, including evaluation framework selection, LLM integration patterns, prompt management and versioning at scale, and model observability
• Worked across the boundary between internal tooling and customer-facing AI products, understanding how requirements differ across those contexts
• Built or significantly shaped an AI evaluation or observability framework in a production environment
• Operated effectively without a team beneath them as a Staff IC whose impact comes from technical leadership and cross-team influence

Benefits

• Hybrid working and the option to work from almost anywhere for up to 90 days per year
• £500 remote working budget to set up your home office space
• $1,000 Learning & Development budget
• 25 days of annual leave plus bank holidays
• An extra day off for your birthday
• Enhanced parental leave: 16 weeks fully-paid leave
• Private Health Insurance (Vitality)
• Full access to Spill Mental Health Support
• Life Assurance covering 4 times your salary
• Cycle to Work Scheme