Principal Technical Product Manager — Quantum-HPC and AI Integration

 

Principal Technical Product Manager — Quantum-HPC and AI Integration 

QuEra Computing, Inc. — Boston, MA (on-site) — Full-time 

About the role 

QuEra's quantum computers (QPUs) will not be used in isolation. Our first gate-based machine Gemini is already deployed as part of the ABCI-Q supercomputer facility at AIST in Japan. Our first FTQC machine Libra, contracted to launch on Amazon Braket in 2028, will live within AWS’ vast managed compute platform and developer ecosystem. The subsequent machines of the Libra class and beyond are already being planned for on-prem and HPC-integrated deployments globally, to deliver value as compute resources inside classical environments: data centers, HPC facilities, AI infrastructures. Furthermore, the AI assistants and agents through which scientists and developers increasingly do their work, will need to harness our QPUs to improve them, and to discover and optimize hardware-efficient algorithms and applications for them. 

We are hiring a Principal Technical Product Manager to own how QuEra’s quantum computers integrate with classical compute, in two directions. Outward: how a QuEra QPU becomes a first-class resource in HPC and AI infrastructure — scheduling, orchestration, hybrid CPU/GPU/QPU execution, data and results flow, and the partner stacks (AWS, NVIDIA, HPE, HPC centers) it has to fit. Inward: how AI systems reach the machine — the interfaces, tooling and workflows through which LLM-based assistants and agentic workflows discover, program and run jobs on QuEra hardware. You will work closely with the teams applying AI inside QuEra’s own machine operations; your focus is the user- and ecosystem-facing side. You own the strategy, requirements and roadmap for both directions, and this product area is expected to grow a team as partnerships convert into deployments. 

What anchors both directions is the application space. You will collaborate with our applications and solutions scientists in the process of selecting two to three killer applications — hybrid quantum-classical computations that generate significant value to industry at the MegaQuOp-to-GigaQuOp scale of QPU — and let these applications drive the requirements for HPC-AI-quantum integration, rather than integrating for its own sake. 

You will join Quantum Computing Services, the team that develops, launches and operates QuEra's commercial machines, where you will work alongside the product managers responsible for these machines as products, and the engineers and scientists who develop them. Year one combines a technical investigation with strategic consequences with a hands-on proof of concept that you lead. 

Year-one focus and deliverables 

1. Killer applications and use-case mapping. Lead the selection, with the applications team, of two to three hybrid applications — in chemistry, materials, optimization, AI-for-science or beyond — that create significant industrial value at MegaQuOp-to-GigaQuOp scale, and map which applications and workflows need which level of quantum-classical co-processing on a three-to-five-year horizon, including the machine-to-machine interfaces and anticipated agentic workflows. Outcome: the applications selected and agreed, and driving the integration requirements. 

2. Proof of concept. One of the killer applications, initially at small scale, running as a hybrid QPU/GPU/CPU workload in a partner HPC or AI environment, and an AI-driven workflow that programs and runs a job on a QuEra machine end to end. You lead this hands-on, with QuEra’s software engineering teams as the architecture partners, surfacing practical problems early. 

3. Ecosystem and value-chain mapping. Who sits where in the HPC and AI stack — cloud providers, accelerator and system vendors, HPC centers, middleware and orchestration vendors, AI platform and agent-framework providers — and each one’s technical vision for quantum integration. Outcome: a complete ecosystem map and a QuEra position on which layers we own, partner on, or leave to others. 

4. Strategic partnerships. Two to three partnerships established at the architecture level — joint architecture, integration model and value-chain positioning — secured through technical buy-in: their architects agreeing that our interfaces and reference architecture are the ones to build against. 

5. Deployment and interface requirements. MVP requirements, derived from the killer applications, for a QuEra QPU as a node in an HPC/AI datacenter — networking, scheduling, identity and access, security and compliance, workload execution model, monitoring, facility parameters — and for the Quantum-Classical Integration Interfaces (APIs, SDKs, orchestration) that connect it. In parallel, a first specification of AI access to the machine: what an assistant or agent needs to discover a device, understand its capabilities and constraints, compose and validate a program, submit it and interpret the result — tool and API surfaces, machine-readable documentation and schemas, guardrails, cost and queue awareness. Outcome: both adopted into the platform and Libra roadmaps. 

Key responsibilities 

• Own the integration strategy and roadmap for QuEra QPUs in HPC and AI environments and for AI interfaces to QuEra machines, with a phased path from simulators on HPC clusters, to joint classical-quantum scheduling, to native quantum accelerators on-site or over high-speed links. 
• Translate the killer applications and workflow needs into a practical quantum-classical execution model and into requirements that engineering can build against, working with engineering as the architecture partner. 
• Contribute the integration and AI-interface perspective to the products this work lands in: the QuEra platform, Gemini, Libra on Braket, and user tooling — so that cloud, on-prem, HPC-integrated and AI-mediated access share one service layer. 
• Build and maintain the partner map across compute, interconnect, cloud and HPC providers, system integrators, middleware and AI platform vendors; lead technical discussions and joint proofs of concept; turn findings into product decisions and build-versus-partner recommendations, and act as the technical product counterpart in partnership negotiations alongside business development. 

What you bring 

• Advanced degree in physics, computer engineering or computational science, with a working understanding of quantum computing and of HPC and AI infrastructure — schedulers, MPI, GPUs, network topology, cloud orchestration. 
• Hands-on experience building or operating the infrastructure that connects users and workflows to quantum or accelerated compute: APIs, gateways, job and resource management, cloud or on-prem deployment. 
• Familiarity with how LLM-based assistants and agentic frameworks consume tools and APIs, and what it takes to make a complex system usable by them. 
• Experience defining requirements, roadmaps and partner strategies in deep tech, HPC or cloud, and running technical partner evaluations or joint proofs of concept with teams at the level of AWS, NVIDIA, HPE or national laboratories. 
• Cross-functional leadership across research, engineering and business development; able to explain quantum-classical integration in operational terms to HPC operators, AI platform teams, executives and partners. 

Nice to have: hybrid quantum-classical workflows (variational algorithms, QEC decoding pipelines, AI-assisted circuit design) or AI-for-science programs; national-lab, government or research customers and their procurement and security environments; quantum cloud platforms, SDKs or developer tooling. 

The annual salary for this role is $180,000-250,000

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.

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