Product Manager, Distributed Computing
About the role
Own the roadmap. Define and maintain the product roadmap for distributed computing. Prioritize against customer value, technical feasibility, and business impact — and defend those priorities with clear, data-driven rationale to engineering, leadership, and go-to-market teams.
Build the first integration and define the native experience. Lead discovery across the distributed computing platforms customers already rely on — HEEDS, ModelCenter, PhysicsX Flux, and cloud-native job services from AWS and GCP — and, based on that discovery, scope and deliver nTop's first integration with the highest-value platform, deferring the rest explicitly for a later phase.
Own the build vs. partner decision for that integration. Shape the first-party headless execution experience — job definition, submission, monitoring, failure handling, and results collection across workstation, on-prem HPC cluster, and cloud — for the workflows this integration unlocks.
Understand usage and consumption patterns. The shift to concurrent-agent pricing is already in motion and will launch ahead of this role. Your job is to understand how customers actually plan, budget for, and scale their usage of compute-intensive workloads, and feed that insight into the ongoing pricing and packaging decisions owned by product leadership.
Measure and instrument. Define the metrics — headless executions, concurrent job volume, time-to-result, integration adoption — and drive the instrumentation needed to track them. Use that data to prioritize and to tell the story of progress to the business.
Work the field. Partner with forward-deployed field engineers and engage directly with advanced users to collect requirements from live workflows, stress-test your roadmap against real constraints (IT governance, security, export control, compute cost), and close the loop between production use and product priorities.
Collaborate across design, UX research, and go-to-market. Work with design and UX research to ensure that scale doesn't come at the cost of workflow clarity. Partner with Marketing, Sales, and CS to translate distributed computing into value that resonates with both engineering teams and the program-level stakeholders who expand usage.
What You'll Do
Own the roadmap. Define and maintain the product roadmap for distributed computing. Prioritize against customer value, technical feasibility, and business impact — and defend those priorities with clear, data-driven rationale to engineering, leadership, and go-to-market teams.
Build the first integration and define the native experience. Lead discovery across the distributed computing platforms customers already rely on — HEEDS, ModelCenter, PhysicsX Flux, and cloud-native job services from AWS and GCP — and, based on that discovery, scope and deliver nTop's first integration with the highest-value platform, deferring the rest explicitly for a later phase.
Own the build vs. partner decision for that integration. Shape the first-party headless execution experience — job definition, submission, monitoring, failure handling, and results collection across workstation, on-prem HPC cluster, and cloud — for the workflows this integration unlocks.
Understand usage and consumption patterns. The shift to concurrent-agent pricing is already in motion and will launch ahead of this role. Your job is to understand how customers actually plan, budget for, and scale their usage of compute-intensive workloads, and feed that insight into the ongoing pricing and packaging decisions owned by product leadership.
Measure and instrument. Define the metrics — headless executions, concurrent job volume, time-to-result, integration adoption — and drive the instrumentation needed to track them. Use that data to prioritize and to tell the story of progress to the business.
Work the field. Partner with forward-deployed field engineers and engage directly with advanced users to collect requirements from live workflows, stress-test your roadmap against real constraints (IT governance, security, export control, compute cost), and close the loop between production use and product priorities.
Collaborate across design, UX research, and go-to-market. Work with design and UX research to ensure that scale doesn't come at the cost of workflow clarity. Partner with Marketing, Sales, and CS to translate distributed computing into value that resonates with both engineering teams and the program-level stakeholders who expand usage.
Who You Are
4–7 years of PM experience in complex, technical B2B software, with ownership of a product area spanning both user-facing workflows and infrastructure or platform concerns.
Experience shipping enterprise software across cloud, on-prem, or customer-managed environments, with working knowledge of modern compute and distributed computing models — containerization, Kubernetes, HPC job schedulers, or cloud-native job execution.
Product-level understanding of scalability, reliability, and security in compute-intensive systems — enough to reason credibly about architectural tradeoffs and work effectively with the engineering teams building the infrastructure.
Strong data orientation: able to define instrumentation requirements, establish leading indicators, and use quantitative evidence to prioritize and communicate.
Preferred Experience with MDO, design space exploration, or engineering orchestration tools (HEEDS, ModelCenter, OpenMDAO, Dakota, PhysicsX Flux, or similar).
Exposure to usage-based or consumption-based pricing models, or experience transitioning a product from seat-based to compute-based licensing.
Background in aerospace, defense, or industrial engineering software, or experience selling into engineering-heavy organizations with complex procurement and IT governance requirements.