Celonis is looking for a Vice President, Solution Engineering (Value Engineering) – DACH.
**About the Company:** Celonis is a German unicorn, a global leader in Process Mining and Process Intelligence. Simply put, their software acts like an X-ray, scanning a company’s business processes (from procurement to finance), identifying “clots,” “fractures,” and other inefficiencies, and then suggesting remedies. The company actively invests in AI to make this analysis even smarter and more precise.
**Their Current Situation and Pain Point:** The DACH region (Germany, Austria, Switzerland) is their home and key market. They are not just looking for a manager, but a “leader of leaders” – a Vice President who will head an entire army of solution engineers. This person’s task is to prove the value of the Celonis product to the largest and most demanding clients. They must understand clients’ strategic goals, translate them into concrete use cases, build roadmaps, charm top management in meetings, and ultimately ensure sales, implementation, and contract expansion. Essentially, Celonis is looking for a super-experienced strategist-psychologist with impeccable business acumen, capable of managing a complex structure and being responsible for multi-million-dollar metrics. The pain point here is obvious: finding such a person is expensive and time-consuming. Training them is even longer. And their departure would be a catastrophe for the region. Scaling the “intuition” and “experience” of a single genius is virtually impossible.
**How Artificial Intelligence Could Solve This:** Instead of searching for a single “superhero,” an “AI Value Engine” could be created – a system that would become a digital twin of this Vice President, but with scalability and without the risk of burnout. This system would take on 80% of the analytical and strategic work, leaving people to do what they do best – build relationships.
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Imagine a dialogue in a Celonis meeting room. Two people are at the table: “Old” – the seasoned IT manager who has seen it all, and “Young” – an ambitious solution architect who believes in code more than in people.
**Old:** (Looking at the job posting printout) Ten years of experience, leadership qualities, vision, ability to communicate with C-level, deep knowledge of finance and logistics… They’re not looking for a person, but a demigod. And even if they find one, they’ll be torn between ten strategic clients, their team, and internal meetings. A bottleneck in the form of a single, albeit brilliant, person. Classic.
**Young:** Why look for one? Let’s build it. Not a person, but a system. Let’s call it the “Digital VP.”
**Old:** (Chuckles) Interesting. And what will your “Digital VP” do? Draw PowerPoint presentations?
**Young:** Not just that. Look how it works, step by step:
**1. Creation of a “Unified Customer Data Lake.”**
We already receive data from the client’s systems for our Process Mining. Let’s add everything else: their public financial reports for 5 years, industry benchmarks, transcripts of all previous calls and meetings from CRM, LinkedIn profiles of key individuals, their quotes in the press. Everything that helps understand not only their processes but also their strategy, pain points, and ambitions. Our “Digital VP” will ingest and link all of this in a couple of hours. A human would need weeks for this.
**2. Development of an “AI Value Discovery Engine.”**
At its core is a combination of our own Process Intelligence Graph technology and an advanced Large Language Model (LLM), trained on thousands of successful business cases. This engine does what takes a human years of experience and intuition:
* **Identifies opportunities:** It doesn’t just find bottlenecks in a process; it immediately correlates them with the client’s strategic goals. “Is your goal to reduce working capital? Here are three points in the `procure-to-pay` process where you’re losing €12 million per year due to invoice delays.”
* **Calculates ROI and builds a business case:** For each identified opportunity, the system automatically generates a complete business case: benefit assessment, implementation cost, potential risks, payback period.
* **Creates roadmaps:** The system offers several options for a Celonis implementation roadmap. For example, “Plan A: Quick Wins” focusing on cases with a payback period of up to 3 months. Or “Plan B: Strategic Transformation” with a long-term impact on the entire supply chain.
**3. Implementation of a “Communications Generator.”**
Based on the conclusions from the previous step, the AI generates a package of materials customized for each meeting participant:
* **For the CFO:** Slides focusing on EBITDA, cash flow, and cost reduction.
* **For the COO:** Dashboards with operational metrics, process efficiency, and throughput.
* **For the CEO:** A one-page Executive Summary linking the solution to the company’s overall strategy and competitive advantage in the market.
The AI can even write cover letters and follow-ups.
**Old:** Sounds good. But C-level wants to see a real person they can trust, not a machine-generated report. The element of trust, empathy… How will you replace that?
**Young:** We won’t. We’ll reduce distrust by changing the human role. The team of engineers and salespeople will stop being “analysts” and “presenters.” They will become “trusted advisors,” armed with the most powerful analytics on the planet. Their job isn’t to crunch numbers in Excel, but to bring a ready-made, machine-validated solution and discuss it at a strategic level. Trust is built not on empty words, but on impeccable preparation. When you bring a client not a hypothesis, but a mathematically verified plan to save millions, trust emerges very quickly.
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### How to Validate AI’s Work?
This is the most important question. The answer to it must be as systematic as the approach itself.
1. **Parallel Launch (A/B Test):** Select 5 strategic clients. For two of them, a “traditional” team works, led by a human leader. For the other three, a team armed with the “Digital VP” works. After 6 months, compare metrics: speed of proposal preparation, depth of business case development, conversion rate to C-level meetings, average deal size, length of sales cycle.
2. **Backtesting:** “Feed” the system data from 20 already closed deals (10 successful and 10 failed) from the past year. The AI’s task is to build roadmaps for them and predict value. Compare its conclusions with what actually happened. How accurately did the AI identify key pain points and potential impact? Did it suggest the same path that led to success?
3. **Insight Quality Assessment:** Create an expert group of Celonis’ most experienced employees. Regularly provide them with two business cases for “blind” evaluation: one prepared by a human, the other by AI. Their task is to assess the depth, completeness, and strategic value of each, without knowing which is which.
Ultimately, a company like Celonis, which sells intelligence for process analysis, looks a bit ironic when it relies on the most “analog,” human processes to sell that very intelligence.
In a world where Celonis teaches machines to understand business, perhaps it’s time to teach business to trust machines. Especially within itself.
Источник: https://www.linkedin.com/jobs/view/4397948834/
