Spendesk · Finance
Head of AI & System
- Paris
Still open on Spendesk's site · checked just now
- Level
- Lead or manager
- Experience
- 6+ years
- Posted
What you'll do
As written by Spendesk · Read the original
Build the AI layer — this is the core of the role
Design and ship the AI applications that power GTM execution: agents, enrichment pipelines, conversation intelligence, automated reporting and decisioning. You build in production, not in slides. You are expected to have a point of view on where AI creates real leverage and where it is theatre, and to prove it with shipped work.
Run engineering discipline on revenue-impacting systems
Bring release management, deployment pipelines, testing and change control to systems that directly carry revenue. Spendesk is a fintech: these systems are held to audit and controls standards, and you own that bar.
Requirements
You may be a good fit if you
Build AI applications yourself. You have shipped LLM-powered workflows to production with measurable business impact — not evaluated vendors, not run pilots that never left the sandbox.
Have an informed and opinionated view on applied AI: what is genuinely useful in a GTM context today, what is not yet reliable enough, and how to tell the difference quickly.
Have deep Salesforce expertise at the object and architecture level: you understand how lead, opportunity, account and quote objects connect, and you have run release management or deployment pipelines.
Typically have 6+ years building and owning GTM or revenue systems, including experience leading or mentoring others. What you have shipped matters more than your years of tenure.
Are pragmatic on build vs buy and can defend the call to both engineers and executives.
Can explain technical trade-offs to non-technical stakeholders without losing them or losing the substance.
Are comfortable operating on systems that carry audit, controls and compliance requirements.
Strong candidates may also have
Production-scale experience with orchestration tooling (n8n, Claude co-work, Make) combined with LLM tooling.
Experience with typical data enrichment and GTM tool stack (incl. Clay, Cargo and prospecting or call recording tools)
Experience in fintech or another regulated environment.
A data engineering background.
As we are an international team, please submit your application and CV in English.
Skills
Working languages
English
Company
Last checked . The details above were extracted automatically; the employer's original posting is the authority.
