About the role We are looking for an Enterprise AI Architect to own the technical shape of an enterprise AI capability for our client.
You will work directly with senior business stakeholders, decide what is worth automating, design and build reusable AI skills, and lead a small team of two Lead AI Solutions Engineers.
This is a hands-on architecture role with a strong consulting and presales component.
What you will do Shape the work Work with senior business stakeholders and domain experts to define objectives, constraints and expected outcomes Identify which processes are worth automating and which are not, and say so when the answer is no Select tools, platforms and approaches for each business problem and defend the choice to both technical and business leadership Shape and present solution proposals: scope, approach, effort, expected impact Own outcomes with a product mindset: adoption, measurable time saved, reliability for real users Own the architecture Own the technical shape of the whole capability: standards, shared components, evaluation and release strategy, backwards compatibility Define what a well-formed skill looks like, what belongs in shared infrastructure and what gets rejected in review Make and justify platform-level decisions: agent harnesses, integration architecture, build vs adopt Apply sound judgement on data handling, security and compliance when working with sensitive HR and compensation data Provide technical leadership to two engineers: review, direction, unblocking Build it Design, build, test and maintain reusable AI skills: instructions, scripts, validation logic, reference data, shared components Write and review production-quality code and own it through review, CI and release Build the evaluation layer: golden cases, acceptance criteria,

regression checks Debug agent behaviour and fix root causes Integrate with the client's platforms and data sources Drive it forward Run pilots with real users, collect structured feedback and ship improved versions Set and enforce standards for authoring, reviewing, versioning and releasing skills Track where AI tooling is going and bring relevant parts into the engagement early Must have Architect-level experience with proven ownership of real systems: module boundaries, reuse, versioning, integration, non-functional requirements Still hands-on: you write and review production code today Strong engineering foundation in at least one modern stack (TypeScript / Node.js is a plus, Python, Java or .NET backgrounds are welcome) Solid engineering practice: version control, code review, automated testing, CI/CD Real LLM-backed systems shipped to real users, not just prototypes Broad hands-on knowledge of the current AI tooling landscape, not tied to a single vendor Working command of agentic patterns: tool use / function calling, MCP, prompt and context engineering, orchestration Experience evaluating non-deterministic systems with test sets and measurable acceptance criteria Judgement on where AI fits and where conventional software is the better answer Direct experience with external clients and senior business stakeholders, including CTO-level conversations Presales experience: shaping, scoping, estimating and pitching solutions Ability to turn ambiguous requirements into a clear design and work without a full specification English C1 Sustained working-hours overlap with US / Western Europe Nice to have Hands-on experience with Claude Code, especially authoring Skills, plugins or MCP servers LLM evaluation tooling (promptfoo, LangSmith, custom harnesses) Consulting or professional services background Exposure to HR tech, compensation

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