Staff Technical Program Manager
Leads end-to-end programs for Crusoe’s managed inference platform, coordinating model engineering, infrastructure, product, and operations teams. The role requires 7+ years of technical program management experience and strong knowledge of production LLM serving, optimization, multi-tenant systems, and GPU readiness.
About the job
Responsibilities
- Own multi-quarter release planning, dependency governance, and executive communication across the Managed Inference platform.
- Drive model version rollouts, inference optimization campaigns, SLA readiness for new GPU hardware, and multi-tenant capacity planning from kickoff through delivery.
- Coordinate across Model Engineering, IaaS, Cloud Foundations, Data Center Operations, and external model providers.
- Identify risks across model serving, reliability, capacity constraints, and vendor timelines.
- Build scalable TPM execution frameworks, maintain real-time dashboards, and deliver data-driven executive updates.
- Own pre-launch planning for model onboarding on new GPU generations, including firmware and driver readiness, CUDA and ROCm stack validation, and inference workload commissioning criteria.
- Drive alignment across engineering, product, and operations leadership, including highly technical stakeholders.
Requirements
- 7+ years of experience as a Technical Program Manager in fast-paced technical environments.
- Experience owning complex programs end to end across engineering and product organizations.
- Working familiarity with LLM inference and model serving, including batching strategies, quantization, and latency, throughput, and cost tradeoffs.
- Familiarity with multi-tenant systems, isolation, quota management, and SLA enforcement.
- Familiarity with fine-tuning and alignment workflows.
- Ability to build execution models in low-structure environments and drive adoption.
- Exceptional written and verbal executive communication.
- Daily use of AI tools to improve program execution, risk detection, and communication.
- Ability to drive alignment across engineering, product, and infrastructure leadership without direct authority.
Nice-to-haves
- Experience with AI inference or training platforms and services.
- Experience governing model onboarding across GPU generations, including firmware, driver, and software stack validation.
- Experience coaching or mentoring junior TPMs.
- Experience with multi-site or globally distributed engineering teams.
- Background at a Series D to Series F company or a hyperscaler AI infrastructure team.
Compensation and Benefits
- Competitive benefits package tailored to local market standards.
- Pension contributions and additional work-life balance perks.
Skills
Llm Inference, Model Serving, Quantization, Fine-Tuning, Multi-Tenant Systems, CUDA, Rocm, Gpu Infrastructure, AI Tools, Capacity Planning
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