Job description

1. Mission of the Role To define, validate, and execute the integration strategy for QuEra’s quantum systems within classical HPC/AI infrastructure — identifying use cases, technical requirements, and the right ecosystem partners across the full value chain. 2. Core Responsibilities A. Use Case Discovery & Technical Research Deeply study academic and industry papers on quantum-classical hybrid workflows, quantum HPC/AI Data center integration, and the accelerations of AI for Science/Quantum discovery via quantum computing. Identify high-value use cases (e.g., quantum chemistry, materials discovery, cryptoanalysis, optimization) relevant to HPC and AI centers Translate theoretical research into practical product requirements — what integration, APIs, or software layers are needed to run these use cases. Collaborate with research teams to maintain technical credibility when engaging HPC customers or partners. Co-design solutions with lighthouse customers to verify the feasibility A. Value Chain Mapping Use the HPC value chain framework (hardware → integration → data center → middleware → workloads → services) to: Map current players (AWS, HPE, NVIDIA, etc.) and their quantum readiness. Identify where quantum computing fits within this chain (e.g., as accelerator hardware, a cloud service, or a hybrid scheduler layer). Define which layers QuEra should own vs. partner — e.g.: Own: Quantum hardware, quantum control stack. Partner: Data center operations, cloud orchestration, middleware, hybrid execution APIs. B. Requirements Definition Gather technical and operational requirements from HPC and AI center operators: Power, cooling, networking, physical integration. Scheduler integration (Slurm, PBS, AWS Batch, Kubernetes). Security, compliance, and monitoring needs. Define product specifications for Quantum-Classical Integration Interfaces (QCII) — the APIs, SDKs, and orchestration layers that enable hybrid workloads. C. Partner Identification & Engagement Build a partner map for each value chain layer: Hardware partners: compute (NVIDIA, AMD, ARM), interconnect (Infiniband), storage (DDN, AWS FSx). Cloud/HPC providers: AWS, Microsoft Azure, Google Cloud, HPE Cray, NVIDIA DGX Cloud. System Integrators: Dell, HPE Middleware/software partners: Slurm Application/industry partners Lead technical discussions and joint proof-of-concept programs with selected partners. Evaluate integration options — e.g., on-prem quantum node vs. cloud-connected quantum service. D. Product Strategy & Roadmapping Define a phased integration roadmap for quantum into HPC centers and AI data center: Simulation stage: Run QuEra simulators on HPC clusters. Hybrid orchestration stage: Enable joint scheduling of classical + quantum workloads. Native quantum accelerator stage: Deploy QuEra hardware within HPC/AI center or connect over high-speed link. Balance build/partner decisions at each stage, ensuring scalability and differentiation. F . Communication & Stakeholder Management Act as the bridge between technical R&D, engineering, business development, and external partners. Create clear documentation (requirements docs, partner briefs, integration specs). Communicate effectively with HPC operators and enterprise customers (translating quantum complexity into operational language). 3. Key Skills and Background Technical Depth : Background in physics, computer engineering, or computational science; understanding of quantum computing principles and HPC architecture (Slurm, MPI, GPUs, network topology). Product Management: Experience defining product requirements, roadmaps, and partner strategies in deep tech or HPC environments. Ecosystem Awareness : Knowledge of cloud and data center ecosystems — AWS, NVIDIA, Intel, HPE, etc. Cross-Functional Leadership: Ability to collaborate with quantum hardware engineers, software developers, and business teams. Partnering & Alliances: Experience building technical partnerships and evaluating technology fit. Communication: Skilled at simplifying deep-technical material for non-specialist executives and partners. 4. Success Metrics A complete map of the HPC/AI ecosystem relevant to quantum integration. Clear technical and operational requirements for deploying QuEra hardware in HPC centers. At least 2–3 strategic technical partnerships (e.g., with AWS, HPE, or NVIDIA). Defined build-vs-partner strategy for each value chain layer. Delivery of hybrid quantum-classical prototype or proof-of-concept within HPC environment. The approximate base salary range for this position is $170,000-250,000. QuEra is committed to cultivating a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

Requirements

Must-haves

Core Responsibilities A. Use Case Discovery & Technical Research
Deeply study academic and industry papers on quantum-classical hybrid workflows, quantum HPC/AI Data center integration, and the accelerations of AI for Science/Quantum discovery via quantum computing.
Identify high-value use cases (e.g., quantum chemistry, materials discovery, cryptoanalysis, optimization) relevant to HPC and AI centers
Translate theoretical research into practical product requirements — what integration, APIs, or software layers are needed to run these use cases.
Collaborate with research teams to maintain technical credibility when engaging HPC customers or partners.
Co-design solutions with lighthouse customers to verify the feasibility
A. Value Chain Mapping
Use the HPC value chain framework (hardware → integration → data center → middleware → workloads → services) to:
Map current players (AWS, HPE, NVIDIA, etc.) and their quantum readiness.
Identify where quantum computing fits within this chain (e.g., as accelerator hardware, a cloud service, or a hybrid scheduler layer).
Define which layers QuEra should own vs. partner — e.g.:
Own: Quantum hardware, quantum control stack.
Partner: Data center operations, cloud orchestration, middleware, hybrid execution APIs.
B. Requirements Definition
Gather technical and operational requirements from HPC and AI center operators:
Power, cooling, networking, physical integration.
Scheduler integration (Slurm, PBS, AWS Batch, Kubernetes).
Security, compliance, and monitoring needs.
Define product specifications for Quantum-Classical Integration Interfaces (QCII) — the APIs, SDKs, and orchestration layers that enable hybrid workloads.
C. Partner Identification & Engagement
Build a partner map for each value chain layer:
Hardware partners: compute (NVIDIA, AMD, ARM), interconnect (Infiniband), storage (DDN, AWS FSx).
Cloud/HPC providers: AWS, Microsoft Azure, Google Cloud, HPE Cray, NVIDIA DGX Cloud.
System Integrators: Dell, HPE

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Keywords to mirror

aiawskubernetesazure

Platform: greenhouse
Effort: quick

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