Technical Program Manager (TPM), Infrastructure

Cursor is hiring a Technical Program Manager (TPM) to partner with our Infrastructure teams to drive COGS attribution, R&D spend efficiency, and resource allocation across Cursor's infrastructure. This role partners with engineering leaders in ML, Infrastructure, and Finance to turn complex cost and capacity data into clear decisions, then drives the programs that land those decisions.

You'll own the programs to enable Cursor to achieve its top business priorities that affect Engineering prioritization, working with an executive or engineering sponsor to scope, drive, and deliver cross-functional initiatives spanning GPU allocation, inference cost management, infrastructure spend attribution, and R&D investment efficiency.

What success looks like

COGs and R&D spend are clearly attributed, understood, and actionable across Engineering and Finance.

GPU and infrastructure allocation decisions are grounded in data and aligned to business priorities.

Cost and efficiency programs run on a predictable cadence with measurable outcomes.

Engineering leaders trust the TPM as a strategic partner who removes ambiguity and drives execution.

Own COGs and R&D attribution programs. Stand up cost attribution across inference, compute, and infrastructure workloads. Partner with Finance and Data to connect spend to products, features, and business metrics. Make cost data actionable for engineering and executive decision-making.

Drive GPU and infrastructure resource allocation. Build frameworks for capacity planning and allocation across 1P models, 3P inference, and experimentation. Run recurring reviews with ML and Infra leadership. Translate business priorities into concrete allocation plans.

Manage technical programs with infrastructure teams. Scope and drive programs in cost optimization, capacity planning, reliability, and migration. Own the operating rhythm for each program alongside a designated sponsor: track progress, escalate blockers, ensure outcomes.

Partner strategically with engineering leaders. Serve as a thought partner on resource tradeoffs, investment prioritization, and operational improvements across ML, Infrastructure, and Finance. Synthesize complex technical and financial information into clear recommendations.