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Job description
PsiQuantum’s mission is to build the first useful quantum computers—machines capable of delivering the breakthroughs the field has long promised. Since our founding in 2016, our singular focus has been to build and deploy million-qubit, fault-tolerant quantum systems.
Quantum computers harness the laws of quantum mechanics to solve problems that even the most advanced supercomputers or AI systems will never reach. Their impact will span energy, pharmaceuticals, finance, agriculture, transportation, materials, and other foundational industries.
Our architecture and approach is based on silicon photonics. By leveraging the advanced semiconductor manufacturing industry—including partners like GlobalFoundries—we use the same high-volume processes that already produce billions of chips for telecom and consumer electronics. Photonics offers natural advantages for scale: photons don’t feel heat, are immune to electromagnetic interference, and integrate with existing cryogenic cooling and standard fiber-optic infrastructure.
Team Overview
PsiQuantum's Applications Software Engineering Team builds tools for quantum algorithm developers: cloud development environments, circuit design tools, and resource estimation systems that help researchers write, simulate, and optimize quantum algorithms for the world's first utility-scale, fault-tolerant quantum computer.
We're hiring a platform engineer who bridges software infrastructure with GPU-accelerated computing, someone who can improve our AWS platform while helping researchers run quantum simulations efficiently on GPU clusters.
Role Overview
We're looking for someone to partner with our existing platform engineer, splitting responsibilities across a growing platform and making it easier for quantum researchers to do their best work.
That platform includes AWS infrastructure, Terraform configs, CI/CD workflows, and the GPU clusters our researchers depend on for large-scale, computationally intensive quantum simulations. There's a real opportunity to shape how all of it evolves.
The right person for this role is comfortable making judgment calls under uncertainty; they will have a lot of latitude, and accountability to match.
Responsibilities
How You’ll Spend Your Time
Platform Engineering (70%)
Own our AWS infrastructure end-to-end and actively shape how it evolves; building, not just maintaining.
Reduce friction in the deployment pipeline so developers can ship without infrastructure blockers.
Harden systems with intention: lock down IAM roles, container images, and authentication flows in ways that reflect a clear understanding of where the real risks are.
Implement monitoring and alerting that catches production issues before users notice them.
Make deployments faster to roll out, easier to roll back, and less prone to failure.
Lead incident response and post-mortems when necessary.
GPU/HPC Bridge Work (30%)
Make GPU clusters and other infrastructure invisible to the researchers running it.
Own CUDA compatibility and driver versions across heterogeneous GPU clusters.
Build standardized SLURM job submission workflows that researchers can use without help.
Package and containerize Python simulation code for reproducible execution.
Monitor job health across utilization, cost, and runtime efficiency.
Experience/Qualifications
Required Qualifications
Experience: 5+ years in Platform Engineering, DevOps, or SRE roles.
Production AWS experience: Built and maintained systems on ECS/EKS, managed multi-account networking (VPCs, security groups), and dealt with real-world infrastructure complexity.
Infrastructure as Code: You've written and maintained Terraform (or Pulumi/CDK) in production, including applying ongoing changes as requirements evolved.
CI/CD: Improved build pipelines in production (reduced build times, increased reliability, made deployments easier to debug), including experience with GitLab CI, GitHub Actions, or equivalent.
GPU/HPC experience: Supported GPU workloads in production environments, including code optimization, CUDA debugging, and job scheduler setup.
Preferred Qualifications
Background in scientific computing, research infrastructure, ML platforms, or early-stage startups (especially research computing vendors).
Security & compliance experience: You've implemented auth systems (Auth0/Okta), managed encryption (KMS), or worked on FedRAMP/compliance-driven infrastructure. FedRAMP experience is a strong plus.
Exposure to quantum computing SDKs (Qiskit, Cirq, PennyLane) or hybrid classical-quantum workflows is a plus, but not required; genuine interest in quantum computing matters more than prior exposure.
What We’re Not Looking For
Candidates focused on enterprise-scale batch computing rather than cloud-native platform engineering.
Platform engineers without exposure to GPU workloads or HPC concepts.
Candidates who prioritize architectural purity over iterative delivery.
PsiQuantum provides equal employment opportunity for all applicants and employees. PsiQuantum does not unlawfully discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, or any other basis protected by applicable laws.
Note: PsiQuantum will only reach out to you using an official PsiQuantum email address and will never ask you for bank account information as part of the interview process. Please report any suspicious activity to
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Worksite address
palo alto, CA, 94306, US
Who can apply
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