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Program Analysis Engineer

SMAROBIX

4.1
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SMAROBIX
Job Type   /   Job Level
Full-time   /   Fresh/Entry Level
Job Location
Dresden, Saxony, Germany
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Program Analysis Engineer (m/f/d)

Location: Dresden, Germany

Type: Full‑time (on‑site preferred, hybrid possible within the EU)


We build software that gives robotics engineers clarity in complex robotic systems. Our tool makes (ROS‑based) robotic systems observable, understandable, and actionable so developers can build safer, more capable robots with confidence.

We are SMAROBIX. A team of 5 founders with complementary skill sets and different cultural backgrounds and a TU Dresden start-up. This role is part of the core team shaping the product’s foundations.


The Role

You’ll work on the static understanding of robotic systems: the point where source code, configuration, and build artifacts become a foundation the rest of the product can rely on. The focus is not on extracting data for its own sake, but on deciding what is valuable, at what level of abstraction, and why those choices remain valid as systems grow in size and complexity.

This is a hands‑on, design‑and‑build role. There is no fixed blueprint: you’ll explore solution paths, test assumptions, and converge on representations that are both technically sound and practical to ship. Much of the work sits near the limits of classical program analysis, and progress depends on clear judgment about those limits and on selecting approaches that hold up in real systems rather than idealized ones.


What We're Looking For

You bring experience with program analysis or language‑centric systems where representation and abstraction matter, whether from compiler construction, static analysis, language engineering, formal methods, or adjacent fields. You’ve worked on problems where understanding meaning across artifacts was harder than implementing the mechanics. Meaning and structure matter more than syntax and form. For you, models matter: what they capture, what they hide, and how those choices affect downstream use. You’re comfortable moving across languages and formats and don’t expect problems to arrive with prescribed methods. Ambiguity doesn’t stall you; it sharpens your questions.

While your focus is analytical, you approach the work pragmatically. The goal is always a reliable, working system. You use AI‑based methods where they help, rely on classical approaches where they’re appropriate, and are clear‑eyed about the trade‑offs between them. In a small team, you communicate clearly, work beyond narrow boundaries when it helps the product, and take responsibility for the outcomes of your design decisions. You know the difference between not knowing yet and not knowing at all, and you're honest about which one it is. Familiarity with robotics frameworks like ROS2, large C++ build systems, or model-driven engineering can give you a head start. However, what we care about is genuine depth and the drive to ship. More broadly, you think in concepts first; tools are secondary to understand the underlying principles well enough to apply them in any context. This applies whether you come from academia, industry, or an unexpected path.


Why This Role

You won’t be maintaining an established analysis pipeline or implementing a predefined model. The foundation exists, but the important representational decisions are still open and visible. That means being critical about scope, timeline, and priorities, not just about the technical solution. The structures you design will sit beneath everything else the product does, and the choices you make will matter for years.

You’ll work closely with the co‑founder responsible for language engineering, with real ownership and room to challenge assumptions. This is a role for someone who wants their thinking, not just their code, to shape a product from the inside. As the team grows, this work naturally evolves into technical leadership through influence and clarity rather than hierarchy.


How to Apply

Send your CV and a short cover letter to jobs@smarobix.com. In your cover letter, tell us about a hard technical problem you worked on and the moment you realized your first approach was wrong: what did you do?

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