Staff Software Engineer (Python)

Qcells North America is seeking a highly skilled Staff Software Engineer (Python) to join their Grid & Energy Services division. This senior technical leadership role focuses on architecting, building, and scaling cloud-native software systems that power next-generation energy management platforms for data centers and industrial environments.

Responsibilities:

• Design, develop, and scale production-grade Python applications for energy and grid management systems, ensuring high performance, reliability, and maintainability
• Architect and deploy cloud-native solutions on Microsoft Azure, including serverless services, storage, messaging, and monitoring, while supporting containerized applications across Docker and Kubernetes environments
• Build and maintain event-driven architectures using Azure Event Hubs and related technologies, while contributing to AI-enabled systems leveraging Azure Foundry agents and agentic orchestration patterns
• Lead technical design efforts, conduct code reviews, and establish best practices, while also owning production support, troubleshooting, and continuous improvements in observability and incident response
• Apply modern AI-assisted development approaches (e.g., vibe coding, spec-driven development) to improve engineering productivity and accelerate delivery

Requirements:

• 8+ years of experience in energy systems architecture, grid infrastructure, or AI-enabled industrial platforms
• Equivalent work experience and a proven track record of technical mastery may be considered in lieu of specific degrees
• Demonstrated success building and operating production-grade software/platforms in regulated or mission-critical environments
• Advanced proficiency in DevOps, CI/CD, and Agile development
• Travel may be required up to 10%, nationally and internationally
• Experience serving as a Staff Engineer, Principal Engineer, or technical lead for large-scale distributed systems or energy platforms
• Expertise in BESS, DERs, renewables, utility operations
• Expertise with cloud-native infrastructure automation, distributed orchestration systems, and scalable data/streaming architectures
• Familiarity with Microsoft Fabric, time-series databases, analytical platforms, and real-time telemetry processing systems
• Exposure to AI/ML systems, LLM-enabled applications, agentic architectures, and AI-assisted engineering workflows
• Experience developing software platforms connected to physical infrastructure, industrial systems, or operational technology (OT) environments