Senior Software Engineering Manager

Key Responsibilities

Team Leadership & Organizational Development

• Lead and mentor a cross-functional software engineering team spanning scientific tooling, analytics infrastructure, and fabrication-support systems.
• Create stronger operational rigor around prioritization, execution, accountability, and project delivery.
• Provide coaching, growth support, feedback, and career development for engineers across varying levels of seniority.
• Help establish healthy engineering culture, team norms, and stronger collaboration practices.
• Serve as a day-to-day thought partner to the VP of Software Engineering while helping create additional leadership bandwidth across the organization.
• Participate in hiring and team scaling efforts as the organization grows.

Technical & Engineering Leadership

• Partner closely with engineers to drive execution across scientific computing, fabrication tooling, analytics systems, and workflow automation.
• Support development of internal tooling and data systems that connect design, fabrication, and device performance workflows.
• Help modernize and operationalize internal tooling that has historically evolved organically through research and prototyping efforts.
• Drive better long-term ownership, maintainability, and lifecycle planning for internally developed systems and infrastructure.
• Help evolve engineering infrastructure and validation frameworks that improve scalability, reproducibility, and operational reliability across hardware development environments.
• Support technical decision-making, architecture discussions, and engineering prioritization while remaining hands-on enough to engage credibly with the team.
• Contribute technically when appropriate, particularly around debugging, architecture reviews, infrastructure improvements, or smaller engineering initiatives.

Cross-functional Collaboration

• Work closely with quantum engineers, physicists, fabrication engineers, and hardware teams to understand operational pain points and evolving workflow requirements.
• Help balance competing stakeholder requests while improving prioritization discipline and long-term planning.
• Partner with fabrication teams as Rigetti continues evolving manufacturing and foundry operations across Berkeley and Fremont.
• Support systems that connect experimental data, fabrication workflows, characterization tooling, and engineering analytics into scalable internal platforms.

Operational & Strategic Impact

• Help transition the team from highly reactive support work toward more proactive engineering planning and scalable systems development.
• Improve processes around technical debt management, prototype ownership, platform sustainability, and operational support models.
• Create better visibility into engineering priorities, roadmap tradeoffs, and team capacity.
• Support ongoing evolution of Rigetti’s scientific and engineering software ecosystem as the company scales hardware development efforts.
• Oversee the development, and architecture of data platforms and modeling tools that combine design files, fabrication process data, and device performance metrics.
• Empower the development and support for tools for design rule checking (DRC), layout-vs-schematic (LVS) checks, and process-aware design verification for quantum devices.

Qualifications

• BS or equivalent degree in Software Engineering, Electrical Engineering, Physics, Applied Physics, or related field; MS or PhD a plus.
• 7+ years of software engineering experience, including 2+ years in a people leadership role, whether formal management or equivalent tech lead capacity.
• Demonstrated experience building data systems, ideally in scientific computing or physics-informed models.
• Demonstrated experience with software systems managing large datasets, metadata, and scalable data pipelines.
• Experience with streaming architectures and tools (e.g., Kafka, Kinesis, Spark Streaming).
• Proficiency in Python; familiarity with JavaScript or TypeScript. Comfort in a scientific computing environment is strongly valued.
• Proficiency with AWS for development and production deployment and distributed computing.
• People leadership ability, including coaching, performance management, and building team culture, whether formal management experience or demonstrated informal leadership.
• Strong communication and stakeholder management skills; ability to represent the team's capacity and push back constructively on internal customer requests.
• Hands-on technical ability; should be capable of making code contributions on an as-needed basis, even if day-to-day focus is leadership.

Nice-to-Have

• Knowledge of quantum device physics, such as superconducting qubits, trapped ions, photonics, or quantum information science.
• Knowledge of quantum control systems and low-level hardware/software interfaces, including cryogenic hardware, RF electronics, and qubit calibration.
• Familiarity with fabrication processes in semiconductor, quantum, or other hardware/lab-based environments.
• Familiarity with EDA tools, process design kits (PDKs), and chip layout software such as KLayout or Cadence.
• Experience with scientific computing platforms, simulation tools, and scientific computing libraries/tools such as NumPy, SciPy, PyTorch, etc.
• Experience applying machine learning to scientific, operational, or hardware systems for prediction, optimization, or anomaly detection.
• Experience with compiled languages such as Go or Rust.