Senior Software Engineer, NeMo Core Platform

NVIDIA•Santa Clara, WA

6d•$184,000 - $356,500

About The Position

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 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 Platform 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 Platform will allow large scale AI consumers to automatically tune their agents to use fewer tokens and rely on more efficient models with better throughput.

Requirements

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

Nice To Haves

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

Responsibilities

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 Platform, SDKs, plugins, jobs, and developer workflows
Building strong test coverage across unit, integration, E2E, Docker, and Kubernetes workflows