
Software Engineer, Back-end (Boulder Opal)
- Sydney, NSW
- Permanent
- Full-time
- Build the backbone of quantum tech: Design, develop, and optimize scalable backend services in Python (with opportunities to work in Rust or C++).
- Own the compiler stack: Maintain and evolve the compiler that translates OpenQASM3 + OpenPulse programs into low-level controller instructions.
- Bridge research and engineering: Work closely with world-class researchers and quantum engineers, translating experimental needs into production-ready code and debugging real-world execution challenges.
- Experiment on quantum hardware: Get hands-on with QPUs, validating compiler output and controller behaviors through real device experiments.
- Engineer for performance: Deliver high-efficiency service-to-service communication using modern protocols (gRPC, GraphQL, REST).
- Raise the bar on quality: Shape and enforce best practices for clean, secure, and reliable code while contributing to robust testing and documentation.
- Shape the future stack: Help define the software practices, tools, and design patterns that will power the next generation of quantum control systems.
- Deliver end-to-end solutions: Collaborate with product, frontend, and infrastructure teams to ship integrated solutions used across Q-CTRL's products.
- Other duties within the Employee's skills and experience, or with reasonable training.
- Bachelor's degree in Computer Science, Engineering, or related field.
- 3+ years of backend software development experience with Python, Rust, C++, or similar.
- Proven experience writing maintainable, testable Python code in a professional setting.
- Strong collaboration and communication skills across cross-functional teams.
- Strong problem-solving skills with a proactive, solutions-focused mindset.
- A curiosity for compiler design concepts or experience working with intermediate representations (IRs).
- Familiarity with OpenQASM3, OpenPulse, Qiskit, or other quantum programming frameworks.
- Hands-on experience with modern APIs like gRPC, GraphQL, or REST.
- Comfortable working with cloud platforms (AWS, GCP, Azure) and cloud infrastructure tools.
- Knowledge of distributed systems, microservices, or database scaling techniques.
- Familiarity with popular Python web frameworks (Django, Flask, FastAPI).
- An eye for data visualization with tools like Plotly, Dash, or Jupyter.
- Experience thriving in a start-up or scale-up environment where speed and collaboration matter.
- Experience designing efficient algorithms, statistical models, or data pipelines to process and analyze large-scale experimental datasets.
- Experience with implementing CPython extension modules for accelerating Python programs.