Head of AI Enablement

Job description

📍 Paris | Full-time | Fluent 🇫🇷 & 🇬🇧 At Bigblue, we're building the logistics backbone for the next generation of commerce. Modern brands sell everywhere: through their own online stores, marketplaces, retail, social commerce, and more. Across every channel, customers expect the same fast, reliable, and transparent experience after they buy. What used to be Amazon's exclusive advantage is now becoming the standard for every ambitious brand. We're helping them get there. Since 2018, we've built a tech-driven fulfilment platform used by 600+ brands, including Muji, Aigle, Scuffers, and Cabaïa. With 200+ Bigbluers across the UK, France, Spain, and Germany, our proprietary tech stack, and a network of 9 warehouses and over 100,000 sqm of fulfilment space across Europe, we ship millions of orders every month. And we're nowhere near done! Backed by €20M+ in funding, we're expanding across Europe and building the operating system that will power modern commerce operations at a global scale. At Bigblue, we hold ourselves to a very high bar: in the quality of our product, the rigour of our operations, and the care we bring to every merchant we work with. You'll be working alongside talented people on real, high-impact problems, in an environment where high standards come with genuine support, ownership, and room to grow. If you want your work to matter from day one, you're in the right place. ## About the Role As **Head of AI Enablement**, you will help Bigblue become the most productive commerce operations company in Europe through AI. Your job is not just to raise AI usage across the business — it is to instill an AI-first mindset, so that every team develops a muscle for reaching for new AI capabilities instinctively, and is enabled to act on those instincts. This role sits at the intersection of internal transformation and external impact. The AI systems and workflows you build internally are increasingly becoming part of Bigblue's external story — shaping how we serve merchants, how our agents engage with them in-product, and how we turn our own operational learnings into time and money saved for the 600+ brands we serve. You will work across disciplines as part builder, part data expert, part product manager, and part business-ops maven, co-developing the cutting edge of AI tooling for the Bigblue team and using it to drive massive change at high velocity. You will start hands-on, shipping the first high-impact automations yourself, then scale a team of AI engineers to multiply your impact across every function. ### What you'll do - Make sure Bigblue teams can deploy AI tools and workflows at the fastest rate in the industry — through enablement and through the development of internal AI products, agents, skills, and tools. - Get non-engineering teams (Account management, Sales, Finance, Transportation, Logistics) leveraging our internal AI stack through focused enablement, product improvements, and individual success stories — surfacing context from our stack, automating merchant-issue triage, billing exceptions, and reporting. - Measure the impact of internal products via (AI-built!) dashboards and QA checks, and iterate based on real user feedback. - Seed an AI-native culture: coach internal "AI champions" and embed templates and practices into team norms. - Build feedback loops that make internal agent performance compound over time — making teams faster and higher-quality at their work, while evolving the external-facing systems that sharpen how Bigblue engages with merchants through AI. - Tackle foundational AI infrastructure with our technical teams: data reliability, managing shared AI skills at scale, and the hard operational problems underneath a truly AI-powered company. - Help package and tell Bigblue's internal AI journey externally — through merchant pitches, conferences, and content — as we productize what we've built for our customers. ### What You Need - 4-8+ years in product management, product ops, BizOps, strategy, technical program management, engineering, or similar — with deep, demonstrated experience using AI to build, ship, and transform work. - Technical fluency with development copilots and low-code/no-code tools (Cursor, Claude Code, Codex, Notion), SQL and BI tools, APIs, scripting, and integrations. - LLM integration depth: tool use, structured outputs, prompt engineering, fallback handling, and cost controls with OpenAI, Anthropic, or equivalent. - Operational empathy: you partner with business teams to deeply understand their challenges and ship rapid solutions. - Strong communicator: you write crisp docs (with AI!) and run persuasive internal training sessions that have lasting impact. - Comfort being steeped in operational and usage data — you decide based on what's actually happening, not just what teams report. - Self-starter with high agency, comfortable with autonomy and ambiguity. Production discipline: fast iteration without fragile systems. ### Nice-to-Haves - Familiarity with departmental workflows in operating teams. - Prior experience in internal enablement or change-management programs. - Curiosity about external applications of internal AI work: customer-facing agents, or commercializing operational learnings. - Familiarity with logistics, supply chain, or operations-heavy B2B environments. - French language skills (our team operates across France, Spain, the UK, and Germany). ### Not for You if - You prefer strategy briefings over hands-on delivery. - You lean toward AI research rather than applied AI work. - You'd rather manage people than building solutions and finding new edges through technology. - You're not interested in the sometimes unglamorous work of making AI systems reliable and scalable. ### What success looks like In your **first 30 days**, you have embedded with at least one internal team, mapped a workflow end-to-end, and shipped something real into production. By **90 days**, you have measurably reduced manual work that was previously just accepted as the cost of doing business, and people in that team can point to it. By **six months**, internal teams are coming to you with problems before they even think to file a ticket; you have a library of reusable patterns that others are building on, and you and the team you have hired set the standard for how AI-powered internal tooling gets built at Bigblue.