Senior Backend Software Engineer

Summary

Join PsiQuantum's Quantum Applications Software Team as a Senior Backend Software Engineer. You will design, build, and maintain automated services and workflows for data-intensive applications in high-performance environments. Collaborate with cross-functional teams to create robust backend systems ensuring efficient operation and seamless scalability. Develop and own essential backend services and APIs, implement scalable job orchestration, and optimize system performance. Contribute to continuous improvement by championing best practices for DevOps and system observability. This role requires a Bachelor's or Master's degree in a related field and 8+ years of relevant experience.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience
• 8+ years of experience in writing and maintaining production software with a bachelors degree or 5+ years of experience with a masters
• Proven experience building production-grade backend services and APIs, ideally in a high-performance or data-intensive context
• Strong proficiency in at least one backend programming language (e.g., Python, Go, C++), with a solid understanding of RESTful or microservices architectures
• Hands-on background in containerization and orchestration (e.g., Docker, Kubernetes), including deployment strategies and load balancing
• Experience with job schedulers (e.g., Slurm, LSF, or PBS) or distributed computing frameworks on HPC clusters or cloud-based systems is highly valuable
• Familiarity with workflow orchestration tools such as Prefect, Airflow, or similar
• Excellent communication and collaboration skills, with the ability to translate complex technical requirements into practical backend solutions

Responsibilities

• Design and maintain backend architectures that integrate with various data pipelines, APIs, and HPC workflows
• Implement workflow engines and scheduling frameworks (e.g., Airflow, Prefect) to automate and monitor multi-step processes at scale
• Ensure reliability and high availability, troubleshooting complex issues across distributed systems, containers, and orchestration platforms
• Collaborate with domain experts to incorporate specialized computational methods or libraries, adapting services to demanding scientific or technical workloads
• Document and streamline processes, maintaining clear and reproducible code for cross-team collaboration and long-term sustainability
• Contribute to continuous improvement by championing best practices for DevOps, performance tuning, and system observability
• Develop and own essential backend services and APIs, facilitating smooth end-to-end workflows for scientific or computational processes
• Implement scalable job orchestration, coordinating tasks across HPC clusters, GPU resources, or other distributed systems
• Optimize system performance, leveraging monitoring and automation tools to identify bottlenecks and streamline critical workflows
• Collaborate with cross-functional teams (e.g., Data Engineering, QA, Product) to drive a cohesive architecture aligned with compliance, scalability, and availability targets

Preferred Qualifications

• Knowledge of DevOps and CI/CD pipelines, plus experience with infrastructure-as-code tools (e.g., Terraform, AWS CDK)
• Exposure to cloud data services (e.g., AWS Glue, Databricks, Snowflake) or event-driven architectures (Kafka, RabbitMQ)
• Performance tuning expertise for GPU-accelerated or HPC-based workloads, including observability solutions (e.g., Grafana, Prometheus)
• Experience in an R&D environment, where research and engineering intersect to develop innovative solutions at scale