Sr Technical Product Manager - HPC Integration

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What the firm says   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, complia

公司寄语   1. 岗位使命 为QuEra量子系统在经典HPC/AI基础设施中的集成制定、验证并执行集成策略——识别全价值链中的用例、技术需求及合适的生态合作伙伴。   2. 核心职责 A. 用例发现与技术研究 深入研究关于量子-经典混合工作流、量子HPC/AI数据中心集成，以及通过量子计算加速AI for Science/量子发现的学术和行业论文。识别与HPC和AI中心相关的高价值用例（例如量子化学、材料发现、密码分析、优化）。将理论研究转化为实际产品需求——运行这些用例需要哪些集成、API或软件层。与研究团队合作，在对接HPC客户或合作伙伴时保持技术可信度。与灯塔客户共同设计解决方案以验证可行性。 A. 价值链映射 使用HPC价值链框架（硬件→集成→数据中心→中间件→工作负载→服务）来：映射当前参与者（AWS、HPE、NVIDIA等）及其量子准备度。识别量子计算在该链条中的定位（例如作为加速器硬件、云服务或混合调度层）。定义QuEra应自研与合作的层级——例如：自研：量子硬件、量子控制栈。合作：数据中心运营、云编排、中间件、混合执行API。 B. 需求定义 从HPC和AI中心运营方收集技术和运营需求：电力、冷却、网络、物理集成。调度器集成（Slurm、PBS、AWS Batch、Kubernetes）。安全性、合规

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