Sr Technical Product Manager - HPC Integration

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 & Road mapping

* 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…