Engineering Manager | Applied AI
AI in this role
Lead the applied AI engineering team at a legal tech company, owning the technical roadmap, agent frameworks, and delivery standards.
We're looking for an Engineering Manager to own AI at one of the fastest-growing AI legal tech companies in Europe. Over 2,000 lawyers use JUPUS every day, and the AI behind it is already in production and already in front of customers. You'd own the team, the technical roadmap, and the standard everything gets built to.
You'll report to our Head of Engineering and lead our AI team. This is a leadership role, not a senior engineering seat with a lead title. You won't be shipping features yourself, and that's deliberate- we want someone whose leverage comes from the team they build and the calls they make.
Your Challenge and Opportunity in This Role
Legal work is document-heavy, judgement-heavy, and almost untouched by AI. We've trained on over a million German court rulings and handled over a million cases, so the hard part isn't proving AI belongs here. The hard part is doing it well enough that a lawyer will put their professional judgement behind the output.
Your job is to make that repeatable. The field throws up something new every week and most of it is noise. We need someone who can tell the difference, turn that judgement into a roadmap, and build a team that can actually deliver it.
Tasks
Leading the team
Make the team better than you found it: hire, mentor, and raise the bar on what good looks like here. Your impact shows up in what they ship when you're not in the room.
Set the engineering standard for AI work: evaluation, testing and observability, and a delivery rhythm that holds up when the pressure is on.
Own delivery at startup pace, without trading away the accuracy lawyers depend on.
Direction and roadmap
Own the technical roadmap: architecture, agent frameworks, retrieval, evaluation and observability. You won't be writing the code, but you will be the person who says whether the design is right.
Partner with product on what gets built: product owns the product roadmap, you own what is technically possible and what it will actually cost.
Separate signal from noise: track how generative and agentic AI is actually evolving, and turn it into decisions rather than slide decks.
Across the company
Get AI into real product workflows, working with design and engineering so it lands as something people use rather than something we demo.
Make the rest of the business better at AI. You're the authority here, and the goal is that other teams get sharper because you're in the building.
Explain AI to people who don't build it, from engineers to the CEO, without dumbing it down or hiding behind it.
Requirements
Leadership
You've run an engineering team and made it better. Direct reports, and specific examples of people who levelled up under you.
You get results through people who don't report to you: product managers, domain experts, other teams.
You've led at pace, on high-performing teams with real deadlines, and you know what to cut.
AI Depth
At least 3 years at a company where generative or agentic AI is central to the product, not bolted onto it.
Teams you've led have shipped agentic systems to production. Prototypes and demos don't count.
You can hold your own on the detail: retrieval quality, evaluation, observability, agent design. You recognise an over-engineered solution when you see one.
Further Requirements
Located within CET +/-2.
Nice to have: a formal background in AI or ML, experience taking a product from non-AI-native to AI-native, familiarity with LangGraph, MCP, LangSmith or Langfuse, or legal tech and other regulated domains.
Benefits
🧠 Real Ownership – The AI function is yours: team, roadmap and standards. No committee between you and a decision.
⚖️ A Market Ripe for Disruption – Agentic AI in a profession that has barely been automated at all, on a product 2,000+ lawyers already use every day.
📈 Growth Stage – €19.5M raised and a team that has nearly tripled in two years.
🏡 Fully Remote – Enjoy the flexibility of working from anywhere
💻 Top Equipment – State-of-the-art MacBook plus all the accessories you need
🏋️ Wellbeing Perks – Urban Sports Club membership to support your healthy lifestyle
If you want to own how AI gets built inside a product that thousands of lawyers rely on every day, we'd love to hear from you.
How we rate this
Engineering Manager | Applied AI at JUPUS rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where engineering management was part of your work. What did you do?
- Tell me about a project where applied ai was part of your work. What did you do?
- Tell me about a project where team leadership was part of your work. What did you do?
- Tell me about a project where technical roadmap was part of your work. What did you do?
- Tell me about a project where mlops was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Engineering Management, Applied AI, Team Leadership, Technical Roadmap, and Mlops. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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