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Salary: EUR 60,000 - 80,000 / annual
Factorial is building the leading AI Business Management Software for companies of all sizes, with over 1,500 employees across Europe, Asia, Africa, and America. This is a founding hire for a new AI Enablement function within IT.
You'll transform scattered AI experiments across Factorial into shared, reusable building blocks—templates, agents, integrations, and safe defaults that enable any team to ship AI solutions in days instead of weeks. This is not a support role; you're architecting the capability that makes AI adoption a company-wide strength.
Key Responsibilities:
- Partner with business teams (Go-to-Market, executives, team leads) to translate loosely-defined ideas into well-scoped, viable AI use cases
- Build and maintain reusable components: templates, skills, agents, MCP servers, integrations, and internal tools
- Design reference architectures and recommended patterns that make the right path the easiest path
- Collaborate with Security to establish safe defaults for identity, permissions, secrets, and data access; provide sandboxes for experimentation
- Maintain a living catalog of internal AI projects and components; connect teams solving similar problems and champion reuse
- Conduct architecture reviews and provide guidance proportional to risk—designed to accelerate, not block
- Enable the broader organization through office hours, guides, hands-on sessions, and community building
- Evaluate tools and vendors; manage costs and overlap; define solution ownership and lifecycle management
- Shape the function's evolution and lay foundations for team growth as the capability scales
You'll report directly to the Director of IT and work alongside IT Systems and Support, partnering closely with Security, Legal & Privacy, Engineering, Data, Procurement, and business teams.
Requirements:
- Solid programming experience and production work with APIs, integrations, identity/auth, and automation
- Real-world experience building with LLMs and agents (tool use, RAG, structured outputs, prompt and context engineering); intensive AI use in your own workflow
- Background in DevOps, Platform Engineering, Systems, or internal tooling; platform mindset and preference for paving roads once over fixing potholes repeatedly
- Comfort with non-technical stakeholders; ability to ask "what problem are we solving?" before "which model?"; skill in scoping ambiguous ideas into buildable solutions that move business goals
- Instinct to find safe ways to say yes to AI adoption; unblocking and accelerating teams rather than defaulting to blocking
- Natural grasp of security principles: least privilege, secrets hygiene, proportional risk assessment
- Founder energy: experience building something from zero (function, platform, practice); ruthless prioritization; motivation by ambiguity
Technical Foundation (not strict requirements):
- Identity & workspace administration: Google Workspace, SSO (SAML/OIDC), directory and access management
- Cloud & infrastructure: AWS, GCP, or Azure; containers, serverless, or infrastructure-as-code (Terraform or similar)
- DevOps practices: CI/CD pipelines, Git-based workflows, scripting (Python, TypeScript, Bash, or similar), monitoring and logging
- Systems administration: SaaS estate management, service accounts, API tokens, secrets management, permissions, audit trails
- AI building blocks: MCP servers, AI skills/plugins, agent frameworks, automation platforms (low-code counts)
- Governance: exposure to AI governance, data governance, or software supply-chain security
- Bonus: experience in Business Technology, IT Systems, Solutions Architecture, or internal business-facing technical roles; teaching, documentation, or enablement program building
Workplace: Office-first, flexible approach in Barcelona. On-site several days per week for collaboration and alignment; remote work supported for deep work and personal needs.
