AI summary: Leads JobTeaser's AI engineering team, managing ML engineers building AI into products and driving internal AI adoption across 200+ colleagues.
JobTeaser – Our young grads got talent.
At JobTeaser, we believe the new generation is the future of business, and that young talent has so much to offer to the professional world and society as a whole.
But finding your path as a student? That’s not easy.
And for companies, understanding and recruiting this generation isn’t any simpler.
That’s where we come in.
JobTeaser is the career space of 800+ European schools and universities, seamlessly integrated into their Student Hubs.
👨‍🎓 For students: a platform and tools to help them find their path, showcase their skills, and land an internship, a work-study program, or their very first job that truly fits them.
đź’ĽÂ For companies:Â privileged access to the best young talent, even before they officially enter the job market.
🏫 For schools & universities: a complete career and recruitment platform to boost students’ employability.
Today, we support over 2 million students and young graduates across Europe.
And you — are you ready to make an impact on the new generation?
Your missions
We’re looking for a Head of AI Engineering to lead JobTeaser’s AI chapter — and make it real.
This is a new role. We’re creating it now because we believe AI is not a feature add-on or a productivity tip. It’s a structural shift in how a tech company works and builds products. For the first time, we’re putting real budget, a dedicated team, and full exec commitment behind it. The bar we’ve set for ourselves is simple: if in six months our teams still work the way they do today, we’ve failed.
You will manage 3 people: 2 ML Engineers building AI into our product, and 1 AI & Automation Evangelist driving how our 200+ colleagues use AI in their daily work. Two distinct mandates, one shared goal. You’ll report directly to the CTPO and be the person who turns our AI ambition into something people can actually feel.
What you’ll do
Own the AI vision
Define and maintain JobTeaser’s AI blueprint across both dimensions: AI embedded in our product (matching, guidance, student experience) and AI transforming how our internal teams work.
Partner with every department to translate ambition into a sequenced, realistic plan — not a slide deck.
Set the success standard, track it honestly, and report progress to the CTPO with a clear picture of what’s working and what isn’t.
Keep the strategy connected to what our users and colleagues actually need, not just what the technology makes possible.
Lead and grow the team
Be the direct manager of 2 ML Engineers and 1 AI & Automation Evangelist.
Run regular 1:1s, give honest feedback, and actively support each person’s development.
Be the technical anchor your ML engineers can look up to — someone whose engineering judgment they respect, not just someone who manages their tickets.
Create the conditions for each team member to go further than they would alone.
Drive internal AI adoption
Work hand in hand with the AI & Automation Evangelist to design and roll out a real internal transformation — not a series of isolated use cases, but a genuine shift in how people work.
Engage managers first, teams second. You know how change actually happens inside organizations.
Identify with department heads where AI creates the most leverage, then make it happen.
Track adoption honestly: active users, workflows changed, time saved. No vanity metrics.
Ship product AI and stay hands-on
Oversee the two ML Engineers on product-facing features: recommendations, matching, student-facing AI tools.
Stay close enough technically to review architecture decisions, challenge model choices, and contribute directly when the team hits a hard problem.
You’re not expected to write most of the code — but you can. When a key prototype needs a second pair of hands or a critical architecture call needs to be made, you’re there.
Keep your technical judgment sharp: you know what current models can and can’t do, you have opinions on infrastructure trade-offs, and you bring that into every important decision.
Technical skills
Strong ML and AI background: you’ve built and shipped models in production, not just run notebooks.
Solid command of Python and modern AI tooling: LLMs, fine-tuning, RAG architectures, vector databases, ML pipelines and deployment.
Hands-on experience integrating LLM APIs into real products — you know what “production-ready” actually means.
You can review code, challenge architecture choices, and contribute directly when the situation calls for it.
Soft skills and mindset
You’ve managed technical teams and know what it takes to make an engineer grow — not just perform.
You have real change management experience: you’ve shifted how people work, not just what tools they use.
You communicate clearly at every level — exec presentation or engineering standup, you adjust without losing substance.
You’re comfortable with ambiguity: this role is new, the playbook doesn’t exist yet, and you’re okay being the one who writes it.
You earn trust from strong IC engineers through technical credibility, and from the rest of the company through clarity and follow-through.
Background
6 to 10 years of experience, combining hands-on technical work (ML engineering, AI systems, software engineering) with team leadership.
Engineering degree or equivalent, with a strong specialization in AI, ML, or Data.
Fluent in French and English.
You stay on top of the AI ecosystem — you bring the information, you don’t wait for it.
At JobTeaser, get ready to…
Your hiring process and the next steps
In order to identify the perfect fit for us (and also for you!), we offer a comprehensive hiring process with the possibility to get to know all your future key team members, and between each step of your process, you will receive constructive feedback from our Talent team.
We are committed to creating a working environment where everyone feels comfortable. We promote diversity within our teams and every application we receive is screened through a unique, pre-established, competency-based process.