Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
-
✓
Employer is on a government sponsor recordThe US Department of Labor certified 486 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
-
?
The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
-
?
No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
-
✓
What Hewlett Packard Enterprise Company paid sponsored hires in similar roles4 certified filings for “Product Manager III” (Project Management Specialists) in CA: $150k–$179k, median $165k.
-
✓
Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 486 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Hewlett Packard Enterprise Company paid sponsored hires in similar roles
- 4 certified filings for “Product Manager III” (Project Management Specialists) in CA: $150k–$179k, median $165k. Most were filed at wage level IV (50%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.
About the role
Principal Product Manager
This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.
Who We Are:
Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.
Job Description:
About the role
HPE Private Cloud AI is the turnkey, NVIDIA co-engineered private AI cloud that lets enterprises run inference, RAG, fine-tuning, and agentic AI on their own infrastructure, delivered as a cloud experience through HPE GreenLake. We are hiring a Principal Product Manager to own a major slice of the platform end to end, from GPU compute and AI fabric to the AI software stack developers use every day. You will set strategy, win the hard trade-offs, and ship the capabilities that make Private Cloud AI the obvious choice over public cloud and neocloud alternatives.
What you'll do
• Own strategy and roadmap for your Private Cloud AI area across GPU compute, AI networking, and the AI software stack, tied to clear revenue, adoption, and utilization goals.
• Define the platform across layers: GPU and accelerator configurations, Spectrum-X and InfiniBand fabrics, storage, Kubernetes orchestration, scheduling, and the curated AI tools customers deploy on day one.
• Make GPUs pay off: drive the features that raise utilization and time-to-value, such as GPU sharing, fair-share quotas, gang scheduling, and multi-tenant isolation.
• Lead the agentic AI roadmap: bring secure agent runtimes, model serving, and developer frameworks into the platform as supported, enterprise-ready experiences.
• Partner deeply with NVIDIA and the open-source ecosystem to co-define integrations, validated designs, and release timing.
• Be the voice of the customer: work directly with enterprise, sovereign, and service-provider buyers to turn their workloads into crisp requirements and PRDs.
• Drive launches end to end with engineering, solutions, marketing, and sales, and track results with data after GA.
Required qualifications
• 10+ years of product management, engineering, or architecture experience, including 5+ years owning AI/ML, HPC, or cloud infrastructure products.
• Hands-on depth in AI compute infrastructure: NVIDIA GPU platforms (e.g., H100/H200, Blackwell), server and rack architecture, power and cooling trade-offs, and sizing for training, fine-tuning, and inference.
• Hands-on depth in AI networking: RDMA, RoCE and InfiniBand, Ethernet AI fabrics (e.g., NVIDIA Spectrum-X), DPUs/SuperNICs, and how fabric design affects job performance.
• Working knowledge of Kubernetes and cloud-native operations, and of how GPU workloads are scheduled and isolated in multi-tenant clusters.
• Track record of shipping complex hardware-plus-software solutions to enterprise customers, from requirements through launch and adoption.
• Strong written and verbal communication; credible with engineers, executives, and customers alike.
• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience.
Preferred qualifications
• AI frameworks and MLOps: LangChain, LangFlow, MLflow, Ray, and SGLang, plus related serving engines such as vLLM.
• GPU schedul
Apply on employer site ↗