Engineering Jobs at NVIDIA with Visa Sponsorship
Engineering jobs at NVIDIA span GPU architecture, AI infrastructure, chip design, and systems software, attracting deep-specialization candidates from around the world. The company has a well-established sponsorship process for international engineers, supporting both nonimmigrant and immigrant visa pathways for qualifying full-time positions.
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Get Access To All JobsINTRODUCTION
As a Senior Engineering Manager for Agentic Systems & Platform Architecture, you will lead the strategy and execution for NVIDIA’s agentic developer platform—deeply understanding how teams across the company build, evaluate, and improve autonomous agents, and turning those evolving patterns into scalable platform capabilities. You will identify gaps and friction, drive rapid proof-of-concepts on emerging agent constructs and ecosystem tools, and operationalize the best approaches into reusable building blocks, integrations, and governance mechanisms that accelerate developer productivity and agent quality. If you’re passionate about staying at the forefront of agent architectures and turning experimentation into real business impact, this role offers a chance to build a platform. This platform helps teams safely ship more autonomous systems at NVIDIA scale.
What you will be doing:
- Track and deeply understand evolving agent development patterns across NVIDIA and the broader ecosystem
- Identify gaps and friction in current agent architectures, and translate insights into a platform strategy that boosts developer velocity and agent quality—backed by evaluations, benchmarking, and feedback loops
- Assess and integrate open source and third-party tools where they add leverage; drive clear build-vs-use decisions
- Architect and integrate high-performance data pipelines, RAG systems, vector databases, and GPU-optimized training and inference workflows
- Lead integration of the AI Data Platform into NVIDIA’s on-prem AI Factory, optimizing GPU-to-storage throughput, data locality, and distributed inference performance
- Establish and enforce robust Agent Governance policies across the platform, covering model/tool usage, data lineage, and ensuring adherence to compliance and Responsible AI frameworks
- Design, implement, and maintain a centralized Agent Safety Toolkit, providing developers with pre-vetted components for input/output guardrails and prompt injection defenses
- Lead and grow a high-performing team along with a multi-functional community to standardize procedures and scale adoption
What we need to see:
- Bachelor’s degree in CS/Engineering or equivalent experience
- 10+ overall years in software engineering, including 4+ years managing high-performing teams
- Strong hands-on experience with evolving agent architectures and open-source libraries; deep expertise in LLM/agent architectures—leading POCs and integrating them into real business use cases with measurable adoption/impact
- Ability to turn fast-moving, ambiguous problem spaces into clear platform strategy, roadmap, and outcomes
- Proven track record building multi-team developer platforms (APIs/SDKs, reusable components, reference implementations)
- Experience building evaluation/benchmarking systems for agent workflows (metrics, regression, feedback loops)
- Strong judgment integrating OSS/3P tools; clear build-vs-use decision-making and integration strategy
- Product approach for safety and governance: controls, audit ability, monitoring, and risk management
- Strong leadership and executive communication (engineering, product, security, research)
Ways to stand out from the crowd:
- Experience implementing enterprise-grade governance for agent systems (controls, audit-ability, monitoring, policy enforcement) in production autonomous workflows
- Demonstrated wins taking new/open-source agent constructs from POC to production adoption, with clear business impact (cycle time, quality, cost, reliability)
- Built and scaled an agent platform or agent developer experience used by multiple teams (SDKs, templates, reference apps, reusable building blocks)
- Clear point of view and real examples on build-vs-use decisions—when to adopt OSS/3P vs build internal primitives—and how to operationalize the choice
- Deep experience with agent evaluation at scale (long-horizon tasks, tool correctness, reliability testing, automated regressions, offline/online feedback loops)
We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Ready to take your career to the next level? Apply now and join the innovation!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 26, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
INTRODUCTION
As a Senior Engineering Manager for Agentic Systems & Platform Architecture, you will lead the strategy and execution for NVIDIA’s agentic developer platform—deeply understanding how teams across the company build, evaluate, and improve autonomous agents, and turning those evolving patterns into scalable platform capabilities. You will identify gaps and friction, drive rapid proof-of-concepts on emerging agent constructs and ecosystem tools, and operationalize the best approaches into reusable building blocks, integrations, and governance mechanisms that accelerate developer productivity and agent quality. If you’re passionate about staying at the forefront of agent architectures and turning experimentation into real business impact, this role offers a chance to build a platform. This platform helps teams safely ship more autonomous systems at NVIDIA scale.
What you will be doing:
- Track and deeply understand evolving agent development patterns across NVIDIA and the broader ecosystem
- Identify gaps and friction in current agent architectures, and translate insights into a platform strategy that boosts developer velocity and agent quality—backed by evaluations, benchmarking, and feedback loops
- Assess and integrate open source and third-party tools where they add leverage; drive clear build-vs-use decisions
- Architect and integrate high-performance data pipelines, RAG systems, vector databases, and GPU-optimized training and inference workflows
- Lead integration of the AI Data Platform into NVIDIA’s on-prem AI Factory, optimizing GPU-to-storage throughput, data locality, and distributed inference performance
- Establish and enforce robust Agent Governance policies across the platform, covering model/tool usage, data lineage, and ensuring adherence to compliance and Responsible AI frameworks
- Design, implement, and maintain a centralized Agent Safety Toolkit, providing developers with pre-vetted components for input/output guardrails and prompt injection defenses
- Lead and grow a high-performing team along with a multi-functional community to standardize procedures and scale adoption
What we need to see:
- Bachelor’s degree in CS/Engineering or equivalent experience
- 10+ overall years in software engineering, including 4+ years managing high-performing teams
- Strong hands-on experience with evolving agent architectures and open-source libraries; deep expertise in LLM/agent architectures—leading POCs and integrating them into real business use cases with measurable adoption/impact
- Ability to turn fast-moving, ambiguous problem spaces into clear platform strategy, roadmap, and outcomes
- Proven track record building multi-team developer platforms (APIs/SDKs, reusable components, reference implementations)
- Experience building evaluation/benchmarking systems for agent workflows (metrics, regression, feedback loops)
- Strong judgment integrating OSS/3P tools; clear build-vs-use decision-making and integration strategy
- Product approach for safety and governance: controls, audit ability, monitoring, and risk management
- Strong leadership and executive communication (engineering, product, security, research)
Ways to stand out from the crowd:
- Experience implementing enterprise-grade governance for agent systems (controls, audit-ability, monitoring, policy enforcement) in production autonomous workflows
- Demonstrated wins taking new/open-source agent constructs from POC to production adoption, with clear business impact (cycle time, quality, cost, reliability)
- Built and scaled an agent platform or agent developer experience used by multiple teams (SDKs, templates, reference apps, reusable building blocks)
- Clear point of view and real examples on build-vs-use decisions—when to adopt OSS/3P vs build internal primitives—and how to operationalize the choice
- Deep experience with agent evaluation at scale (long-horizon tasks, tool correctness, reliability testing, automated regressions, offline/online feedback loops)
We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Ready to take your career to the next level? Apply now and join the innovation!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 26, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
See all Engineering Jobs at NVIDIA
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Get Access To All JobsTips for Finding Engineering Jobs at NVIDIA
Align your credentials to NVIDIA's specializations
NVIDIA's Engineering hiring skews heavily toward GPU computing, CUDA, deep learning frameworks, and hardware architecture. Tailor your resume to match the specific technical stack of the team you're targeting before submitting applications.
Target teams with established sponsorship histories
Not every Engineering team at NVIDIA hires internationally at the same rate. Research which divisions, such as AI platforms or silicon engineering, have the most active international hiring and focus your outreach on roles in those groups.
Understand the H-1B cap and NVIDIA's filing cycle
NVIDIA files H-1B registrations in the March lottery window. If you receive an offer after cap season, ask your recruiter about cap-exempt paths or whether an October start date is feasible for your situation.
Prepare your degree equivalency documentation early
NVIDIA Engineering roles typically require a bachelor's or master's in a specific engineering or computer science field. If your degree is from outside the U.S., get a credential evaluation ready before interviews move to the offer stage.
Ask about E-3 eligibility if you hold Australian citizenship
NVIDIA sponsors the E-3 visa for Australian nationals in specialty occupation Engineering roles. Unlike the H-1B, the E-3 has no lottery and can be filed at any time of year, making it a faster path to a start date.
Find open Engineering roles at NVIDIA using Migrate Mate
Locating verified sponsorship-eligible Engineering postings at NVIDIA manually is time-consuming. Use Migrate Mate to filter NVIDIA's active openings by visa type and Engineering function so you're only applying to roles with a clear sponsorship pathway.
Frequently Asked Questions
Does NVIDIA sponsor H-1B visas for Engineers?
Yes, NVIDIA sponsors H-1B visas for qualifying Engineering roles. The company participates in the annual H-1B cap registration process each March and files petitions for selected candidates. If you're already in H-1B status with another employer, NVIDIA can also file an H-1B transfer, which lets you start without waiting for a new cap year.
How do I apply for Engineering jobs at NVIDIA?
Applications go through NVIDIA's careers portal. Most Engineering roles list specific technical requirements, so tailoring your application to the team's focus area, such as silicon design, AI infrastructure, or software systems, improves your chances. You can also browse NVIDIA's sponsorship-eligible Engineering openings filtered by visa type on Migrate Mate before applying directly through the company.
Which visa types does NVIDIA commonly use for Engineering roles?
NVIDIA sponsors H-1B visas for most international Engineering hires, along with the E-3 visa for Australian nationals and EB-2 or EB-3 Green Card pathways for longer-term employment. For engineers on OPT or STEM OPT, NVIDIA can typically support the transition to H-1B. The right visa depends on your citizenship, degree level, and the specific Engineering role.
What qualifications does NVIDIA expect for sponsored Engineering positions?
NVIDIA Engineering roles typically require a bachelor's, master's, or PhD in electrical engineering, computer science, or a closely related field. Sponsored positions are specialty occupations under USCIS standards, meaning the degree requirement must match the role's duties. Deep technical expertise in areas like GPU architecture, CUDA programming, or machine learning systems is commonly expected at the mid-to-senior level.
How do I plan my timeline if NVIDIA offers me an Engineering role with H-1B sponsorship?
H-1B cap petitions must be filed after the March lottery selection, with employment starting no earlier than October 1. If you're on OPT, confirm your expiration date allows you to bridge the gap. Premium processing through USCIS, currently adjudicated within 15 business days, is available and worth discussing with your recruiter if your start date is time-sensitive.