Senior Software Engineering Manager

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.

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.

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.

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.

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.

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.