AI Implementation Manager

You are the bridge between our AI and our customers' reality and the main interface between enneo and your dedicated clients. Part strategist, part project lead, part AI whisperer.

As AI Implementation Manager, you own the entire journey from first handshake to live production. You don't just "onboard" customers — you transform how their service operations work. You get deep into their processes, configure our platform to fit their world, and make sure the AI delivers real, measurable impact from day one.

• Make AI Real for Our Customers: You take our platform out of the demo and into the trenches. You work directly with service leaders, IT teams, and operations managers to understand their pain points, map their processes, and design an implementation that actually works — not in theory, but in their daily chaos of thousands of tickets and calls.
• Own the Implementation End-to-End: From kickoff to go-live and beyond. You configure AI Agents, set up workflows and business logic, train the system on customer-specific knowledge, and iterate until the automation runs like clockwork. You don't hand off — you see it through.
• Bridge the Gap Between Technology and Business: You translate complex AI capabilities into language that operations leads and C-level stakeholders understand. You build trust, manage expectations, and consistently demonstrate value. When a customer asks "what can AI actually do for us?" — you show them.
• Drive Continuous Improvement: Go-live is just the beginning. You monitor performance, identify optimization opportunities, and push adoption from Copilot to Copilot+ to Autopilot. You turn good implementations into great ones.
• Shape the Product From the Front Lines: Nobody knows our customers' needs better than you. You feed insights back to our product and engineering teams, helping us build a platform that's not just technically impressive but operationally indispensable.

Must-Haves:

• Strong project management skills — you can run complex, multi-stakeholder implementations without things falling through the cracks. You've done this before.
• Technical acumen — you don't need to write production code, but you understand how software systems work, how APIs connect, and you're not intimidated by configuring complex logic. You can talk to developers and business people in the same meeting.
• A genuine fascination with AI and what it can do. You stay curious, you experiment, and you understand that this technology is reshaping entire industries right now.
• Outstanding communication skills — fluent German and English, spoken and written. You can run a workshop with a 50-person service team in the morning and present results to a CEO in the afternoon.
• A true startup mindset — you thrive in environments where not everything is documented, processes are still being built, and your initiative directly shapes how things work. You don't wait for someone to tell you what to do.

Nice-to-Haves:

• Previous experience in customer service operations, contact centers, or service transformation projects.
• Experience in consumer-facing regulated industries (energy, finance, insurance, banking, utilities).
• Background in AI/ML implementation, conversational AI, or enterprise SaaS.
• Experience working with enterprise clients (complex stakeholder landscapes, long decision cycles, high compliance requirements).

We aim to keep the process efficient:

1. Intro / Vibe Check (30 minutes)*: A short conversation to get to know each other, talk about your background, and discuss the role and what we’re building at enneo.
2. Technical & Implementation Discussion (45–60 minutes): Conversation with our CTO about how you approach real customer implementations. We will discuss topics like system integrations, APIs, enterprise SaaS rollouts, and how you manage complex stakeholder environments.
3. Founder Conversation (30–45 minutes): Final conversation with our CEO to discuss expectations, how you would work with customers, and how you would help scale AI implementations at enneo.

*In some cases, the first conversation may already include both the initial introduction and the technical/implementation discussion.