As a Back-end Engineer on the Boulder Opal Scale Up team, you’ll be at the forefront of building the software backbone that powers the future of quantum technology. You’ll work side by side with brilliant engineers and researchers, designing and delivering scalable, high-performance systems that bring groundbreaking science into the real world.
From SDKs to cloud-based platforms, your work will shape the tools researchers and customers use every day. You’ll not only develop world-class backend systems but also help translate cutting-edge research into production-ready solutions, bridging the gap between quantum experiments and reliable software.
Suppose you’re excited about building robust systems, tackling complex problems, and exploring the edge where software meets quantum physics. In that case, this is your opportunity to make a real impact in one of the most exciting fields in technology today.
What you'll be doing:
- Build the backbone of quantum tech: Design, develop, and optimize scalable backend services in Python.
- Build impactful systems: Design, develop, and optimize scalable backend applications that power real-world quantum technology.
- Engineer for performance: Create high-efficiency service-to-service communication using modern protocols.
- Bridge science and engineering: Work hand-in-hand with researchers to translate cutting-edge research code into production-ready solutions, while sharing engineering best practices.
- Deliver end-to-end solutions: Partner with product, frontend, and infrastructure teams to ship integrated features used across Q-CTRL’s products.
- Shape reusable architectures: Develop product features that promote flexibility, reuse, and scalability across multiple business cases.
- Other duties within the Employee's skills and experience, or with reasonable training.
Ideally you'll have:
- 5+ years of backend engineering experience with Python, Rust, C++, or similar.
- A track record of collaborating across research and engineering to solve hard technical challenges.
- Strong understanding of domain driven design, service oriented architecture, asynchronous processing, and software testing.
- Experience designing, implementing, and maintaining efficient algorithms and statistical models.
It would be fantastic (but not essential) if you bring:
- Experience with modern APIs (gRPC, GraphQL, REST) and Python web frameworks (Django, Flask, FastAPI).
- Exposure to cloud platforms (AWS, GCP, Azure), infrastructure management, and CI/CD pipelines with container orchestration (Kubernetes).
- Familiarity with observability tools (Prometheus, Grafana, Tempo, CloudWatch) and data orchestration/warehousing platforms (Airflow, Snowflake, dbt).


