We are looking for a Senior Software Engineer to help build NeMo Helix, NVIDIA’s product for developing, evaluating, deploying, and operating AI systems at scale. This role is for a senior engineer/architect for our Core team which owns and ships an open source plugin-based AI platform for running and optimizing Agents targeting multiple compute backends (local/docker, Kubernetes, Slurm, etc.).
As AI systems become more autonomous and more deeply integrated into real workflows, teams need robust APIs and orchestration systems for running, monitoring, and optimizing Agents at scale. Increasingly, the users of these systems are themselves autonomous or semi-autonomous Agents. The NeMo Helix group is building a sophisticated agent execution framework to enable agents to automatically run hundreds of experiments in parallel to find the most efficient agent architectures for our customers. This is important product engineering research for making agents more sustainable. AI systems are not yet nearly as efficient as they can be, and systems like NeMo Helix will allow large scale AI consumers to automatically tune their agents to use fewer tokens and rely on more efficient models with better throughput.
What you'll be doing:
- Working in a product research environment where we place big bets on where the future is heading, adapting in real time as we build alongside an industry that is constantly evolving with us. This means fast iteration, high ownership, pragmatic decisions, and performance-minded implementation under production constraints
- Designing an Agentic Execution system that are flexible enough to work in many environments (local, k8s, Slurm, on prem / air-gapped)
- Provide senior technical leadership through design reviews, code reviews, mentoring, and ownership of ambiguous cross-component problems
- Building and maintain our Core Platform APIs for running jobs, storing data, entities, secrets, and RBAC and Auth
- Extending our flexible Plugin Architecture that makes it easy for many teams and external customers to install new capabilities into our system
- Building in the open in our OSS repo, keeping up the high standards that the open source community demands
- Shipping code at the speed of light with an unlimited token budget using best in class agentic coding tools
- Improving reliability, observability, debuggability, and performance across NeMo Helix, SDKs, plugins, jobs, and developer workflows
- Building strong test coverage across unit, integration, E2E, Docker, and Kubernetes workflows
What we need to see:
- BS, MS, or equivalent experience in Computer Science, Computer Engineering, or a related technical field
- 10+ years of professional software engineering experience building production systems
- Comfort working in a very fast and ambiguous environment
- Exceptional communication, both verbal and written. This includes the ability to produce and review high quality architectural RFCs, and to discuss them clearly with the right level of technical detail for the right people (Engineer, Product, Marketing, etc.)
- Strong system design skills, with a pragmatic flexibility and phenomenal instincts to invent robust systems quickly without over-complicating. Strong understanding of reliability, scalability, security, and performance tradeoffs in production infrastructure
- Experience with distributed systems, cloud-native services, containers, Kubernetes, and job orchestration
- 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
- Ability to work independently, define technical scope, break down ambiguous problems, and drive work across team boundaries
Ways to stand out from the crowd:
- Experience building, deploying, and iterating on production agentic AI systems at scale in Kubernetes
- Experience with sophisticated plugin architectures
- Strong ability to connect technical evaluation work to business outcomes, product quality, user experience, reliability, or operational efficiency
- Experience with enterprise AI systems where measurement, regression testing, observability, governance, and continuous improvement are required for production deployment
184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
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.Skills Required
- Bachelor’s degree, master’s degree, or equivalent experience in Computer Science, Computer Engineering, or a related technical field
- 10+ years of professional software engineering experience building production systems
- Comfort working in a fast-paced and ambiguous environment
- Exceptional verbal and written communication skills, including producing and reviewing architectural RFCs
- Strong system design skills and understanding of reliability, scalability, security, and performance tradeoffs in production infrastructure
- Experience with distributed systems, cloud-native services, containers, Kubernetes, and job orchestration
- 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
- Ability to work independently, define technical scope, break down ambiguous problems, and drive work across team boundaries
- Experience building, deploying, and iterating on production agentic AI systems at scale in Kubernetes
- Experience with sophisticated plugin architectures
- Ability to connect technical evaluation work to business outcomes, product quality, user experience, reliability, or operational efficiency
- Experience with enterprise AI systems requiring measurement, regression testing, observability, governance, and continuous improvement for production deployment
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
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Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
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Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
