Jobs / United States / Nvidia Corporation

Nvidia Corporation

Senior Software Engineer, Agentic Systems

5 Locations Posted today

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Skills this job asks for

Product managementPythonDockerKubernetesLeadershipCommunication

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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 2,374 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 Nvidia Corporation paid sponsored hires in similar roles701 certified filings for “Engineer Senior Systems Software” (Software Developers) in CA: $173k–$214k, median $190k.
  • 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 2,374 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 Nvidia Corporation paid sponsored hires in similar roles
701 certified filings for “Engineer Senior Systems Software” (Software Developers) in CA: $173k–$214k, median $190k. Most were filed at wage level IV (82%) — 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

We are looking for a Senior Software Engineer to help build NeMo Platform, NVIDIA’s product for developing, evaluating, deploying, and operating AI systems at scale. This role will focus on NeMo Evaluator, which helps teams understand whether changes to AI agents are making those agents better. As AI systems become more autonomous and more deeply integrated into real workflows, teams need practical infrastructure for observing behavior, measuring progress, catching regressions, and iterating with confidence. Our roadmap is increasingly focused on agentic development and automated agent improvement: giving teams the infrastructure they need to compare versions, understand behavior, and make empirically grounded improvements over time. What you'll be doing: • Design and implement Python-first APIs, SDK workflows, and plugin interfaces for building, measuring, and improving agents across multiple runtimes and product surfaces • Build reusable systems for observing behavior, measuring progress, detecting regressions, and turning runtime evidence into product decisions • Build systems for ingesting, normalizing, validating, and analyzing agent execution data and evaluation datasets • Partner with research, product, platform, and infrastructure teams to integrate agentic capabilities broadly across NVIDIA agent runtimes and developer workflows • Help turn emerging agent development and improvement techniques into reliable, reusable product capabilities • Improve reliability, observability, debuggability, and performance across NeMo Platform, SDKs, plugins, jobs, and developer workflows • Build strong test coverage across unit, integration, E2E, Docker, and Kubernetes workflows • Drive “speed of light” engineering: fast iteration, high ownership, pragmatic decisions, and performance-minded implementation under production constraints • Provide senior technical leadership through design reviews, code reviews, mentoring, and ownership of ambiguous cross-component problems What we need to see: • BS, MS, or equivalent experience in Computer Science, Computer Engineering, or a related technical field • 5+ years of professional software engineering experience building production systems • Excellent Python engineering skills, including API design, typing, testing, debugging, performance analysis, and maintainable software design • Experience designing SDKs, libraries, plugins, CLIs, or other developer-facing interfaces • Experience with distributed systems, cloud-native services, containers, Kubernetes, or job orchestration • Strong understanding of reliability, scalability, security, and performance tradeoffs in production infrastructure • Experience with structured data modeling and validation systems such as Pydantic, typed schemas, event/trace models, or SDK-generated types • Ability to work independently, define technical scope, break down ambiguous problems, and drive work across team boundaries • Clear communication skills and a track record of collaborating with engineering, product, research, or customer-facing teams Ways to stand out from the crowd: • Experience building, deploying, and iterating on production agentic AI systems where evaluation was used to measure and improve real product outcomes • Experience designing evaluation workflows for heterogeneous agents, including tool-using agents, RAG agents, workflow agents, coding agents, or long-running autonomous systems • Experience integrating evaluation capabilities across multiple products, runtimes, or internal platforms, especially through Python SDKs, plugins, or shared developer tooling • Strong ability to connect technical evaluation work to business outcomes, product quality, user experience, reliability, or operational efficiency • Experience wit

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