Applied AI Engineer

About the role

You are our first dedicated Applied AI Engineer, and your remit is the whole business: sales, customer success, marketing, delivery, finance and operations. Anywhere someone is doing work a well-designed agent or workflow should be doing, that's yours.

Critically, you are the architect. Work will reach you as a problem, not a specification — "renewal risk is invisible until it's too late", "delivery handovers lose information every time", "this report takes two days a month to produce". From there the system is yours: interrogate the brief, work out what it should actually do, choose the approach and the tooling, design how it sits across the platforms we already run, build it, launch it and own it in production. Nobody will hand you a solution design, and nobody will review your architecture for you. That is the job, and it's why we're hiring at this level rather than for a pair of hands.

It also means you'll work directly with the people who own the results your systems affect — short feedback loops, no committee, and a very clear read on whether what you built actually mattered.

Wide surface, real autonomy, and everything you ship gets used the next morning.

What you'll own

• Production AI agents and routines — taking prototypes to monitored, reliable, production-grade systems, starting with the commercial suite already in flight
• A reusable skills and prompt library for drafting, analysis, reporting and document generation, shared across functions
• The internal integration layer across monday.com, HubSpot, Aircall, Microsoft 365 and Guidde
• Commercial systems — pipeline and portfolio reporting, account health signals, onboarding flows, executive business review generation
• Marketing and go-to-market systems — content pipelines and campaign operations
• Delivery and operations systems — project reporting, resourcing visibility, document and scope production, handover automation
• Finance and administrative workflows — reconciliation, reporting and the recurring manual work that currently eats hours
• Documentation, standards and internal enablement — everything you build is documented, supportable and teachable to the people who use it

What we're looking for

We are optimising for AI fluency and creative problem solving over depth of traditional software engineering. You need to be able to build and maintain what you design, but we care more about how you think about a problem than how elegant the code is.

• Demonstrable fluency with modern LLM tooling — agent design, prompt and context engineering, MCP, evaluation and iteration. Claude and Claude Code experience is a strong advantage
• Model-agnostic judgement — the ability to assess Claude, OpenAI, Gemini and whatever lands next on capability, cost, latency and fit, pick the right one for each job, and re-test that decision as the landscape shifts. We are not loyal to a vendor; we are loyal to the outcome
• Strong automation and integration skills across SaaS APIs (REST, webhooks, authentication) and iPaaS platforms such as Make, Zapier or n8n
• The technical ability to ship and support production systems: Python/TypeScript, git, cron, CI/CD, Linux, error handling and logging
• Confidence working with data across systems — extracting, transforming and reconciling records from multiple platforms
• The ability to architect a solution from a vague problem statement — scoping it, choosing the approach, and being able to explain and defend the design to both technical and non-technical stakeholders
• A portfolio of things you have actually launched, that other people still use. Tell us about them
• The judgement to push back on a brief, propose a better approach, and know when not to build something
• Comfort working across unfamiliar business domains — you'll be automating finance one month and delivery the next, and you'll need to learn each well enough to design for it
• Written English strong enough to work asynchronously with a senior team across time zones, and the security-mindedness to work inside tenant boundaries with customer data

Nice to have: monday.com or HubSpot platform experience (apps framework, GraphQL APIs); prior work inside a consultancy or agency; light front-end for internal tools; experience with documentation or video documentation tooling.

What this role isn't

No billable client delivery. No model training from scratch. No general IT helpdesk. Your entire remit is making one company measurably more effective.

What success looks like

• First 30 days — access established, the systems we already run documented and understood, and the backlog assessed and sequenced with your recommendations on what ships first
• First 90 days — Existing AI based workflows optimised and performing in a production environment— monitored, logged and reliable without supervision — plus two new systems live and in daily use
• First 6 months — the same patterns extended beyond the commercial team into at least two other functions, with a documented, reusable foundation others can build on
• First 12 months — a maintained internal AI platform spanning the business, with measurable hours returned across functions and a clear roadmap you own