Lead Forward Deployed Designer, Artificial

• You are a designer who thrives in ambiguity and constraints, someone who can bring structure, judgement, and clarity to complex, real-world delivery
• You likely have experience in enterprise/B2B software where:
• The design system already exists
• The hard part is framing the right problem and navigating stakeholders
• Solutions must work within meaningful technical and organisational constraints
• You understand technical concepts fluently. Part of the role would involve writing code (with plenty of LLM and human assistance) using our in-house DSL (Domain Specific Language). We don’t want you to be an engineer, but we do need you to be comfortable reading and writing some code, reasoning about how a configurable system behaves, and understanding what the platform can and can’t express, well enough to hold a credible conversation with engineers and to explain these constraints to customers when necessary
• You have managed designers. You’re comfortable with line management of a small team (roughly three to five people) and have hired designers before. Early on, you’d do this hands-on yourself; as the function grows, you’d manage the FDDs who follow
• Insurance or Lloyd’s experience is a plus, but is not a requirement. We care more about how you think about complex platforms and stakeholders than about prior domain knowledge, which you can learn here
• Strong problem-solving skills
• Think you don’t meet every requirement? Please apply anyway. We value potential as much as experience, and we know that raw talent counts

Desirable

• Today, a key part of delivery has no clear owner: problem framing before configuration begins
• On the customer side, there are rarely UX specialists - only domain experts and sponsors who describe needs as pre-formed solutions
• On our side, configured workspaces are built by Forward Deployed Engineers (FDEs) in our Transform team: experts in the platform, accountable for shipping to a deadline, but not trained designers
• Our Platform teams have design expertise but are often too far removed from individual implementations to influence the moments that matter most
• The result is pretty predictable: we move quickly into “how” before we are confident about the “what” and “why.”
• Your mandate is to slow down at the right moment and make sure we’re solving the right problem - then help the team implement the best platform-valid solution
• This is a founding role. You would be the first Forward Deployed Designer (FDD) at Artificial, hired into an enabling function within the Platform team, with the mandate to define how the function works and to build it out. Later, FDDs would join the Transform teams in hands-on client roles: you’d take part in hiring them (with our support), then line-manage them directly
• You would work closely with the Transform team and customers throughout discovery and delivery. In practice, that means:
• Establish the FDD function. Define the operating model, the patterns, and the ways of working from scratch
• Grow and manage the team. Take part in hiring subsequent FDDs and line-manage them as they join
• Join customer + FDE sessions early (problem framing and discovery), not only at reviews once decisions are already fixed
• Translate requests into problems. For example, turn “we need a confirmation button before this step” into:
• The user behaviour driving the request
• Two or three platform-valid approaches
• A recommendation, with trade-offs explained
• Prototype and test ideas quickly using the most effective medium (written specs, wireframes, workflows, or light code). We care more about clarity and platform realism than polished artefacts
• Provide credible pushback when the customer’s proposed solution doesn’t address the underlying problem
• Codify patterns and precedents so knowledge moves from individual memory into shared team infrastructure
• Level up the FDE team’s design instincts over time. You shouldn’t be the only person who can think about UX across the two teams; part of the job is coaching, so the capability can spread
• Use workspace signals (e.g. session data and call analysis) to surface risks early - before they become escalations