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München, Bayern, Deutschland
Hybrid
Available
When people use our technology to "bridge the gap" between the physical and digital worlds, they don’t just capture reality - they create a new one. In this new reality, they are smarter, more productive, more streamlined, and more creative - because they have the digital foundation to build the world they want to live in.
That’s what NavVis offers in all our products and services: the tools to not just map the world as it is, but to pave the way to a better future. To forge something new. Physical or digital, there is only one reality. And it’s the reality NavVis empowers people to build better.
As a Senior Software Quality Engineer, you will shape how quality is engineered across the complex, data-intensive processing systems of NavVis IVION. Rather than acting as a final testing gate, you will build the test strategies, automation, data, observability, and feedback loops that help the team identify risks early and deliver reliable software with confidence. Your scope will cover individual processing components as well as end-to-end workflows, including advanced 3D data ingestion, processing, streaming, and web rendering.
ABOUT THE TEAM
You will join the IVION Data Foundation team, a growing group of engineers and domain specialists responsible for the spatial-data backbone of NavVis IVION. The team transforms reality-capture data into a fast, streamable, high-fidelity spatial intelligence layer, spanning data ingestion, semantic enrichment of point clouds and images, algorithmic cleaning and fusion, and the data structures that enable efficient storage, streaming, and 3D rendering.
The team works in a hybrid model, combining remote work with dedicated in-office days each week. We value spending time together in person, especially when tackling complex or ambiguous problems. We make extensive use of agentic coding tools, such as Claude Code, to amplify our impact and accelerate development. We develop on Linux or macOS, and our production systems run on Linux.
Establish and evolve the team’s quality-engineering system, including test strategy, standards, tooling, data, and feedback loops, while making quality a shared responsibility across the engineering team.
Design and build sustainable automated coverage for complex, large-scale data-processing workflows, focusing effort where it delivers the greatest reduction in risk, cost, and recurring manual work.
Ensure robust quality across advanced 3D capabilities, from point-cloud and Gaussian Splat ingestion through processing, streaming to the final web experience.
Identify the areas where the system is most likely to fail, including data edge cases, performance bottlenecks, orchestration issues, evolving interfaces, and cross-team dependencies, and translate those risks into effective test coverage.
Treat quality holistically by validating functional correctness, user experience, reliability, scalability, performance, and resource efficiency under realistic operating conditions.
Develop a scalable test-data strategy for large, complex, and continuously evolving spatial datasets, file formats, and data structures.
Enable developers and other team members through clear guidelines, practical test protocols, tooling, and quality signals so they can perform effective PR and release validation, while contributing hands-on manual testing selectively where additional expertise is most valuable
Several years of professional experience owning and advancing quality engineering for data-intensive, high-performance processing systems
Hands-on experience designing measurements and quality signals for correctness, runtime, scalability, and resource consumption across CPU, GPU, memory, storage, and I/O
A systematic, data-driven approach to investigating failures, diagnosing regressions, and distinguishing deterministic defects from effects caused by concurrency, parallelism, or non-deterministic system behavior
Solid Python skills and practical experience with PyTest or comparable test frameworks, combined with the ability to read unfamiliar code and build a strong understanding of complex systems
Practical experience working with Linux, Docker, and Kubernetes in development or production-like environments
Sound engineering judgment and a holistic mindset, applied to prioritizing between functional quality, performance, reliability, delivery speed, and infrastructure cost
Interest in applying AI beyond personal productivity to improve QA systems and automation, for example, turning observability signals into diagnoses, test cases, fixes, or pull requests
NICE TO HAVE
C++ knowledge
Experience testing 3D web-rendering technologies such as WebGL, WebGPU, or Three.js
Experience with browser automation tools such as Playwright
Your recruiting partner for this role is Lenka (she/her). You can expect to go through a screening call, and up to 4 rounds of interviews, where we would love to discover your passion and interests, introduce you to who we are and what drives us, and finally understand how we can potentially add value to each other's growth.
NavVis’ unwavering commitment to fostering an inclusive and diverse workplace has laid the foundation for our incredible growth. We thrive on the collective strength of our people who come from diverse backgrounds. We respect and value every experience associated with race, gender identity, sexual orientation, nationality, religion and disability. We do not discriminate on the basis of any of these, or other identities, and strongly encourage everyone to apply.
Together with you, we build NavVis!
If you need assistance at any stage of the recruiting process due to a disability, please reach out to your recruiting partner(s) for this position.