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Senior Technical Program Manager, Forward Deployed Engineering

NVIDIA· Architect, Solutions
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Hybrid (US, CA, Santa Clara)$184k - $287.5kFull-timePosted 4d ago

About the role

Lead the technical strategy and execution of NVIDIA’s Forward Deployed Engineering engagements across NVIDIA Nemotron and NVIDIA Cosmos, turning AI use cases into production through strong technical depth, engagement strategy, and ecosystem alignment.

Responsibilities

  • Sets the technical direction for each FDE engagement and serves as the main point of contact for NVIDIA, the partner, and the end customer; defines scope, milestones, and success criteria and keeps all parties aligned from first conversation to production.
  • Automates program work using AI agents and agentic workflows (SOWs, status updates, meeting synthesis, risk flags); builds and reviews agent workflows.
  • Collaborates with FDEs and partner engineers to understand use cases, data, evaluation approach, and deployment path to scope engagements and identify risks early; shapes data and program strategy and makes technical decisions.
  • Defines processes and artifacts to make engagements repeatable; creates playbooks, templates, and reusable agent workflows; manages delivery and coordinates with legal, partnerships, data sharing, and compute access to clear blockers.
  • Identifies where NVIDIA adds value across partners, use cases, open model builders, and cloud providers; aligns priorities with FDEs, sales, partners, and solutions; reports progress to leadership; communicates insights to Product, Engineering, and Research.

Qualifications

  • Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field, or equivalent experience.
  • 6+ years in technical program management, solutions architecture, forward deployed engineering, or technical customer delivery, including leading complex multi-party programs from concept to production.
  • Working knowledge of the LLM post-training lifecycle (data, evaluation, fine-tuning and reinforcement learning, deployment) with depth to engage credibly with ML engineers; practical comfort with Python and cloud/GPU infrastructure.
  • Hands-on experience using AI agents and agentic workflows to run programs (planning, tracking, reporting) and the judgment to validate outputs.
  • Experience across open model, post-training and harness, and cloud provider ecosystems; multi-company engagements with executives.
  • Experience shaping SOWs and agreements, working with legal/procurement, and handling data sharing and governance.
  • Proven ability to manage risks, dependencies, and decisions with incomplete information; define metrics and drive to outcomes.
  • Clear communication of complex technical ideas to engineers and C-level executives; excellent organizational skills.

Skills

Required:Technical program managementSolutions architecturePython

Benefits

  • equity
  • benefits (as per NVIDIA benefits page)
Last updated Oct 23, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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