Forward Deployed Engineer
About the job
- You have taken quantitative models for real operations problems into production, using optimization, simulation, or both.
- You have done this more than once, end to end, and at least one of those models still runs without you.
- You have recent, substantial hands-on experience writing and operating production Python.
- You identify the assumptions and constraints that decide the result, and clarify them with the customer before building.
- You are comfortable working directly with plant managers and controllers, and can explain a model to people who will never read the code.
- You have experience working with messy industrial data and cleaning it.
- You have experience working in a team with shared standards, not only on your own projects.
- You can make technical decisions independently and explain the trade-offs.
- You have German at C1 level or above and fluent English; you can run a customer meeting in German and write a specification in English. Both are required because customer conversations happen in German.
- You have an existing work visa for Germany.
- Take the customer's decision problem and own it end to end: build the model on their data and stay with it until management trusts the result enough to act on it.
- Build models that decide what gets produced when, on which machine, and at what stock level.
- Turn how customers actually make planning decisions into models a machine can compute.
- Catch inconsistent and incomplete ERP and Excel export data, including numbers that cannot be right, before the customer notices them.
- Decide what remains project work and what becomes product when planning problems recur across customers in different forms.
- Turn ambiguous customer needs into models that get used rather than handing over after the concept.
- Make scope and trade-offs explicit with customers as priorities change.
- Travel regularly across the DACH region for decisive customer conversations; travel is not expected every week.
About the company
Circonomit provides a browser-based decision-intelligence platform that links environmental data with financial metrics for corporate planning. Its SaaS modeling toolbox uses a visual interface, reusable data blocks, and a semantic modeling layer, and can be added to existing systems like Excel and SAP to map cause-and-effect and calculate financial and environmental impacts. The product supports applications such as green controlling, emissions calculations, modular life cycle assessments, and sustainability reporting, especially for enterprises in the DACH region. Its goal is to help companies reduce costs, save time, and lower liability by turning sustainability into a competitive advantage through data-driven decision making.
Company Size
1-10
Company Stage
Seed
Total Funding
$3.1M
Headquarters
Aachen, Germany
Founded
2022
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Simplify's Take
What believers are saying
- July 8, 2025 seed funding from Vorwerk Ventures, Fund F, and PUSH VC extends runway.
- August 2026 hiring for data, product, and operations research roles signals active expansion.
- The website shows live scenario, optimizer, and controlling products for enterprise buyers.
What critics are saying
- SAP and Microsoft can bundle adjacent planning features and crush standalone adoption.
- Eleven active jobs in August 2026 signal heavy build-out before clear scale.
- Without proprietary customer data, Circonomit risks becoming a generic modeling layer.
What makes Circonomit unique
- Circonomit adds a semantic modeling layer to Excel and SAP, not another dashboard.
- Its strategic digital twin translates value-chain cause-and-effect into calculable decisions.
- Founded by Dana Aleff and Erik Müller, it targets complex industrial planning problems.
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Benefits
- Hybrid Work Options
- Company Equity
- Gym Membership