Forward Deployed Engineer (m/f/d) - AI Automation, internal

Stellenbeschreibung:

About Us

Rabot Energy is an independent provider of dynamic electricity tariffs with 100% green energy. Through our innovative procurement strategies, we ensure both ecological sustainability and cost optimisation in home energy management. By passing on wholesale electricity market prices directly to our customers, we are able to reduce their electricity bills by an average of 35%.

Owners of electric vehicles and smart meters benefit particularly from our dynamic electricity tariff, as they can automatically charge their vehicles at home when electricity prices on the exchange are especially low. In the Rabot Energy app, charging preferences can be easily set and current market electricity prices can be tracked in real time.

With our intelligent charging solutions, we actively contribute to increasing the share of renewable energy in Germany’s overall electricity consumption.

Our vision is to give every customer the opportunity to manage their energy consumption in a smart way while conserving the environment and natural resources. By offering smart charging and energy management solutions, Rabot Energy actively helps drive the energy transition forward. With this idea, we have already won the trust of over 100,000 customers.

Why Now?

Every team at RABOT has work that eats time: manual, repetitive, error‑prone. The tools to automate that work now exist — what’s missing is someone who walks into a department, actually understands the process, and ships the automation. We’ve built one of the highest AI‑adoption engineering orgs in the DACH region. Now we take that across the entire company.

We’re not looking for someone to write reports about what AI could do. We’re looking for someone who builds it.

Your Mission

You go from department to department — Finance, Operations, Customer Service, Sales — and turn manual work into working automation. You sit with the people who own a process, understand it end to end, and build the AI‑powered solution that takes the repetitive part off their plate.

Concrete example: Finance’s dunning flow (Mahnwesen) — automated screening for collections, cancellations and dunning letters. You map it, you build it, they get their time back.

But this role is more than shipping tools. Every team knows their own processes; what they lack is the time or the know‑how to automate them. Your job is to bring both. You show each team what’s genuinely possible with AI, you earn their trust, and you leave them faster than you found them. You’ll be a builder first — hands‑on, in the code — working alongside a junior engineer, and you report directly to the CTO.

Your Results

Month 3 (Ramp‑up)

You understand RABOT’s departments, their core processes and our AI tooling (Claude, Claude Code, our data stack) well enough to run a process‑discovery session on your own.
You’ve shipped your first automation into production — something a team feels immediately.
A first department trusts you enough to ask for the next thing.

Month 6 (Performance)

You’ve delivered automations across at least three departments, each with measurable time saved.
Teams come to you with problems instead of waiting to be asked.
Your junior runs smaller automations independently, because you’ve set the pattern and shared the how.

Month 12 (Scale)

You’re the person the whole company associates with “this used to take hours — now it doesn’t.”
Automation is a habit across departments, not a one‑off project.
The way you discover, build and hand‑off processes is documented and repeatable, so it scales beyond you.

Who We Are Looking For

Builder, not adviser: You don’t stop at a slide showing what’s possible. You open the editor and ship the thing. “It works in a demo” isn’t enough — it has to run in production and survive contact with a real team.
Process detective: You can sit with someone in Finance or Ops, follow a messy real‑world process end to end, and see exactly where the repetitive work is. You ask “what steals the most time from you?” before you propose anything.
Trust builder: You walk into a department that doesn’t know you and leave with them on your side. You understand that the hard part isn’t the automation — it’s getting people to change a process they’ve owned for years. You lead with service, not with “IT is here to fix you.”
AI‑native: AI coding and agent tools (Claude, Claude Code, Cursor) are already part of how you work every day. You have a nose for where an LLM is the right tool and where it isn’t.
Bias to ship: You’d rather deliver a rough automation that saves a team an hour a day this week than design the perfect platform for next quarter.

Professional Requirements

A proven track record of automations shipped to production — not prototypes, not proofs of concept.
Strong engineering fundamentals: comfortable with Python (or similar), APIs, and working with data.
AI coding and agent tools (Claude, Claude Code, Cursor) are part of your natural workflow.
Fluent in German and English — you’ll be sitting with German‑speaking teams to understand their daily work, so German is non‑negotiable for this role.

Bonus

A forward‑deployed, solutions‑engineering or consulting background — you’ve walked into an organization you didn’t know and made it work.
Hands‑on with process mining, workflow automation or RPA tooling.
Energy sector or another regulated, process‑heavy industry.

What We Offer

Impact: When a colleague stops doing an hour of manual work a day, it’s because of what you built. You see the effect of your work on real people, fast.
Ownership: You decide where the biggest wins are and how to build them. You are reporting directly to the CTO.
Culture: Transparent feedback. We celebrate mistakes as long as we learn from them.