Build it on the floor with us.

The role

Oppr is still founder-led: the CEO carries the pipeline end to end and closes every deal himself. That got our first customers in, and it does not scale. We need someone to take the front end off his hands, so we are hiring a junior seller with real drive as our first seat in Sales.

Your first focus is the hardest and most valuable part of an early-stage sale: getting us in the room. You prospect a small, named list of European operators, open the conversation, and earn the site visit, so that the founder walks into meetings you created. In the beginning the CEO stays close and runs the deal from the demo onward, while you keep the top of the funnel full and organised and learn the industry deal by deal.

This grows deliberately. As we build a repeatable sales playbook together, you take on more of what comes after the meeting: discovery, the demo, and steadily more of the deal itself. This is a ground-floor seat with room to become a genuine full-cycle seller, not a hire capped at booking meetings.

The deal has a shape you will start to recognise: an operations-manager champion who wants stable output and to stop being woken at night, an economic buyer who only asks whether it moves the P&L, plus IT and Procurement to clear. Reaching the right people and keeping several conversations alive at once, multithreading, is the craft you will build.

What you will do

• Own the top of the funnel. Prospect a small, named list of European operators, run outbound that actually lands, and turn cold accounts into booked site visits for you and the founder.
• Get us in the room, and stay in it as you ramp. Open the account, earn the site visit, and take on more of what follows, discovery and the demo, as you learn the motion.
• Multithread the buying committee. Reach past the first friendly contact to the champion, the economic buyer, and the people who can block a deal, and keep several threads warm at once.
• Keep the pipeline honest and organised. A clean, qualified snapshot per account, so nothing goes cold and every opportunity stays comparable. This is how the CEO coaches you, not CRM theatre.
• Build the playbook with the founder. Our sales motion is real but young. You run the play, then help sharpen it from what actually works in front of buyers, and hand landed deals cleanly to our Continuous Improvement Engineers at kickoff.

What you bring

• You open doors. You are genuinely good at, and not afraid of, cold outreach and starting conversations with people who did not ask to hear from you. This is the core of the role and the thing we will look at hardest.
• You get things done. Bias to action, resourceful, organised, and you close the loop. You keep many threads moving at once without dropping them, and you take the next action without being told.
• Early in your career, and hungry. A year or two of selling, or a track record that shows you will outwork the room. We index on drive and coachability over years or a big-logo CV.
• Hunger to learn a new industry fast. No waste or manufacturing background required: we will teach you the industry. Bring the selling instinct and the curiosity to walk a plant and ask good questions.
• Structured and AI-first. You keep your pipeline clean because a forecast the founder cannot trust is worse than no forecast, and you are keen to work with modern tools to do it faster.
• Coachable against a forming playbook. Strong enough to have opinions, humble enough to run the play before rewriting it.
• Bonus: experience and language. Any B2B selling into technical or considered purchases is a head start, and so is Dutch, since we sell to Dutch customers now, and German, our next market. English is our working language.

What you are measured on

At the start, meetings created: qualified conversations and booked site visits with the right accounts. As you ramp and the playbook firms up, that broadens toward pipeline created and, in time, closed deals. Euros are the through-line at Oppr, and your work is what fills the top of that number.

How this role grows

This is a ground-floor seat with an obvious ceiling above it. You start by getting us in the room; as you ramp you carry more of the deal, and as the team grows there is an option to grow into a full-cycle closing seat and, in time, Sales Lead: carrying the number, the forecast and the weekly euro roll-up while coaching the sellers who come after you. It is a seat we would far rather fill from within.

The role

You have run improvement projects on a live plant. You know that the analysis is the easy part. Getting operators to trust the project, getting honest data out of a running line, and making the improvement survive after you leave, that is the actual work.

We built Oppr because most improvement projects die at that last step. The gain is real for a quarter. Then the person who knew why leaves, the SOP was never updated, and the line drifts back.

You are not implementing software. You are running an improvement project inside a customer's plant, and Oppr is what you run it with. The hard skill is decomposition: a customer arrives with a frustration, an idea or a KPI that will not move, and you break that into parts, decide which part is measurable, choose what data would prove it, design the smallest intervention that tests it, and structure the whole thing so it repeats without you. That is systems thinking applied to a live process. If you have run DMAIC, built a control plan, written standard work or closed out a Kaizen properly, you already think this way. Here you do it inside a platform, at speed, at a different customer every few months.

Most of the work is on site at customers across the Netherlands, Germany and Western Europe. When you are not on a plant floor you work from The Hague or from home. This is a job you do with the customer, not to them. Operators can tell within five minutes whether you speak their language, and nothing works if they decide you do not.

To be explicit, because the title has confused people before: this is not a software engineering role. You will not write production code and you will not sit behind a desk. If you want to build the platform rather than use it to fix a plant, this is the wrong seat.

What you will do

• Find the problem that is worth solving. Walk the line and talk to operators, shift leaders and engineers. Separate the stated problem from the real one.
• Build the hypothesis. Use our internal analysis tooling on the customer's machine data and operator observations to work out what is likely causing it.
• Design the project. Scope a ten-week Proof of Value that will prove or disprove that hypothesis. Defined measurement, defined pass or fail, agreed with the plant before you start.
• Get the operators in. Design what they need to capture, explain why it matters to them, and stay on the floor until it becomes routine. Nothing else in this list works if this step fails.
• Gather and analyse. Real data from a running line, not a clean dataset. You work out what it is telling you.
• Propose the improvement. In production terms and in euros. Downtime, scrap, changeover, first pass yield.
• Lock it in. This is the part most projects skip. Turn the finding into updated standard work, a check, a trigger or an SOP inside the platform, so the improvement holds after you leave and the lesson is available to the next shift and the next plant.
• Repeat, faster. Then the same cycle across the rest of the site, using the playbook you wrote doing it the first time.

What you bring

• Real shop-floor credibility. Process engineer, plant engineer, mechanical engineer, improvement engineer, production engineer, maintenance engineer. The title matters less than the floor time. This is the one thing we cannot teach.
• You have owned an improvement project end to end. Problem definition, plan, operator involvement, data, analysis, improvement, and standardisation. Not a piece of one.
• Structured problem solving. RCA, DMAIC, Lean, Six Sigma, TPM, 8D, whichever school you come from. And you can say what your improvements were worth, and how you knew.
• You have got operators to change how they work and make it stick. You know the technical part was the easy half.
• Comfortable with data. You can take a messy machine dataset and a set of operator observations and form a defensible hypothesis.
• Comfortable around industrial data systems. MES, SCADA, historians, OPC UA, PLC tags, IoT platforms. You do not need to build them. You need to get data out of them and know what it means, and to be confident enough with software to configure a platform, read a data flow and find the problem yourself.
• You can run several customer projects at once, with your own planning and risk view, and hold your own with an operator, a maintenance lead and a plant director on the same day.
• BSc or MSc in mechanical, process, chemical, industrial or automation engineering, or equivalent time served. Fluent English, Dutch strongly preferred, German a plus, and happy to travel to customer sites regularly.

What you are measured on

Improvements that hold. Getting the plant to a first proven result inside the ten-week Proof of Value, stated in euros the plant agrees with, and locked into standard work so the line does not drift back once you move on. Then the same cycle again, faster, across the rest of the site.

How this role grows

This is a ground-floor seat with a clear path into Implementation & Support Lead: owning delivery quality, the playbook and the engineers who come after you. It is a seat we intend to fill from within. You also get a direct line to the CEO and to the roadmap, so what you see in the field ships.

The role

The engineering team is five developers deep, building fast. The CTO knows industrial operations from the inside and is good at the kind of problem-solving that has no existing playbook. What is not there yet is serious academic depth: the kind that knows when a problem needs a knowledge graph versus a relational table, reaches for the right optimisation model, and can reason about why a time series forecast is drifting without being walked through it. That is what this seat is for.

The CTO brings the operational intuition. You bring the depth. You will not be expected to have walked a plant or to know how a procurement approval process works inside a large manufacturer. You will be expected to understand ontologies from first principles, to have the modelling range that lets you tackle a scheduling problem one week and a forecasting challenge the next, and to know the stack — Go, Python, Google Cloud — well enough to own it.

The inputs Oppr processes are as varied as the plants it serves. ERP data from SAP and similar systems. SCADA feeds. Data historians with tens of millions of rows of timestamped process values. Spreadsheets, images, voice, knowledge bases. Each of these is a different world with different data quality realities. You will own how we connect to all of them and how we get reliable, structured data out the other side.

You will also shape how the team codes. We are building an AI-first engineering practice — using tools like Claude seriously, not as a shortcut. You will set the patterns, review the output, and hold the bar. The five developers on the team code fast; your job is to make sure what they ship is also right.

What you will do

• Own the solution stack end to end. Know every layer — the Go backend, the Python data and AI work, the cloud infrastructure, the integrations — and make sure it holds together as a coherent, maintainable whole.
• Solve the hard modelling problems. Resource optimisation, scheduling under constraints, time series forecasting, machine learning on real industrial signals. Bring the academic toolkit and use it on problems that actually matter.
• Build and own the integrations. Connect Oppr to the real industrial world: ERP systems, SCADA, data historians at scale, spreadsheets, images, voice. Each integration is a small product in itself, not a one-off script.
• Establish the AI-first coding practice. Set the approach, the review patterns, and the quality standard for AI-assisted development across the team. Own what comes out of those sessions.
• Keep the knowledge graph and asset ontology sharp. The graph is at the core of how Oppr models industrial reality. You are responsible for the depth, the correctness, and the design decisions behind how it grows.

What you bring

• Academic depth. MSc, PhD, or a track record that makes the equivalent clear. We have people who build fast; we need someone who also thinks rigorously, and who reaches for the right algorithm rather than the first one that works.
• Knowledge graphs and ontologies from first principles. Not a tutorial familiarity — the kind that lets you design a schema from scratch, argue the trade-offs, and know when a graph is the wrong model entirely.
• Modelling range. Time series forecasting, optimisation, linear programming, machine learning, scheduling under resource constraints. You do not need to be a specialist in all of them, but you need to know which tool fits which problem and be able to implement it.
• Full-stack capability across Go and Python. Python for data and AI is your natural home. Go does not need to be your first language, but you need to be able to read, extend, and take ownership of a Go backend.
• AI-first as a craft. You use Claude and similar tools extensively and thoughtfully. You know where they make mistakes. You can set the review discipline that keeps AI-assisted code reliable at team scale.
• You are near The Hague and in the office three to four days a week. The hard problems get solved in the room.
• Bonus: exposure to industrial data systems. Data historians, SCADA, ERP integrations, or time series at industrial scale. You do not need it on day one — but the curiosity to go deep on how a plant actually generates data is what we will look for.

What you are measured on

The depth and reliability of what gets built. Hard problems solved correctly. Integrations that hold under real industrial data. A knowledge graph that models customer reality accurately. And a team that ships AI-assisted code you would genuinely sign off on.

How this role grows

This is a senior individual contributor seat with a clear ceiling above it. As the engineering team grows and the product matures, there is a natural path toward Technical Lead: setting architecture direction, owning the quality standard across the team, and shaping how engineering at Oppr is done. It is a seat we intend to fill from within.