Senior AI Engineer

Location:

Barcelona (office-first) ·Team: IT — AI Enablement (new function) ·Reports to: Director of ITDo you want to help every team at Factorial build with AI, faster, safer, and without reinventing the wheel?

Teams across Factorial already use AI every day: assistants, automations, agents, internal tools. We're creating a new AI Enablement function inside IT to turn that energy into a shared, secure, reusable capability — and you'll be its founding hire.

We're looking for someone who: Loves building, and loves it even more when what they build makes other people faster.

Feels at home talking with a sales leader in the morning and shipping an MCP integration in the afternoon.

Believes the best guardrail is a well-paved road, not a locked gate.

Ready to be part of the challenge?

Senior AI Enablement Engineeryou'll turn scattered AI experiments into shared building blocks the whole company can build on — templates, agents, integrations, and safe defaults that let any team ship in days instead of weeks. This is not a support ticket queue. You're not writing the same automation five times for five teams; you're the reason nobody has to. About the TeamThis role sits inside IT (team name to be confirmed), reporting directly to our Director of IT. You'll work alongside IT Systems and Support, and partner closely with Security, Legal & Privacy, Engineering, Data, Procurement, and business teams across the company. IT keeps a hypergrowth company running. This role adds a new capability to it: making AI adoption something we do well together — with shared building blocks, clear patterns, and safe defaults — instead of something every team figures out alone.

You'll start as a team of one, with the mandate to shape how the function works: its tools, its standards, its ways of working. As the function proves its value, you'll build the team that grows around it. What You'll Be DoingPartner with business teams: work directly with Go-to-Market, executives, and team leads to turn loosely-defined ideas into well-scoped, viable AI use cases — understanding the business need before proposing the technology.

Build reusable building blocks: create and maintain the templates, skills, agents, MCP servers, integrations, and internal tools that let teams build in days instead of weeks.

Design reference architectures: define recommended patterns, stacks, and practices for internal AI solutions, so the easiest path is also the right one.

Pave secure paths: design safe defaults for identity, permissions, secrets, and data access together with our Security team, and provide sandboxes where teams can experiment with confidence.

Champion reuse: keep a living catalog of internal AI projects and components, connect teams solving similar problems, and make reuse the default.

Review and guide: help teams get architecture, dependencies, permissions, and code right, with reviews proportional to risk — designed to accelerate, not to block.

Enable people: run office hours, write guides, deliver hands-on sessions, and grow a community of internal AI champions — technical and non-technical alike.

Shape the function: evaluate tools and vendors, watch cost and overlap, define how solutions are owned and maintained over their lifecycle, and lay the foundations of the team you'll build as the function grows.

What Are We Looking For?

Builder's core: solid programming experience and production work with APIs, integrations, identity/auth, and automation. We care about what you've shipped more than the specific stack you used. AI as a daily habit: you've built real things with LLMs and agents (tool use, RAG, structured outputs, prompt and context engineering) and you use AI intensively in your own workflow.

Platform mindset: a background in DevOps, Platform Engineering, Systems, or internal tooling; you'd rather pave the road once than fix the same pothole ten times.

Business translation: you're comfortable with non-technical stakeholders, you ask "what problem are we solving?" before "which model?", and you can scope an ambiguous idea into something buildable that moves a real business goal forward.

Enabler by default: when someone wants to use AI, your instinct is to find the safe way to say yes — you unblock, guide, and accelerate teams so the company's objectives keep moving, and you treat blocking as a last resort for real risk.

Security by design: least privilege, secrets hygiene, and healthy skepticism about dependencies come naturally to you — applied with judgment, proportional to risk.

Founder energy: you've built something from zero (a function, a platform, a practice), you prioritize ruthlessly, and ambiguity motivates you rather than paralyzes you.

Technical Foundation (Not Strict Requirements)Identity & workspace administration: Google Workspace administration,