Senior Software Engineer, Agentic Systems

Reposted 17 Days Ago
5 Locations
In-Office or Remote
184K-357K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The Senior Software Engineer will develop and integrate AI systems, focusing on improvement and evaluation. Responsibilities include designing APIs and monitoring tools, optimizing performance, and collaborating with cross-functional teams.
Summary Generated by Built In

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 NeMoStack services, 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 with enterprise AI systems where measurement, regression testing, observability, governance, and continuous improvement are required for production deployment

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you’re passionate about leading breakthrough AI research and building exceptional teams that shape the future of computing, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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.

Applications for this job will be accepted at least until June 7, 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.

Skills Required

  • BS, MS, or equivalent experience in Computer Science, Computer Engineering, or a related field
  • 5+ years of professional software engineering experience
  • Excellent Python engineering skills
  • Experience designing SDKs, libraries, or plugins
  • Experience with distributed systems, cloud-native services, or Kubernetes
  • Strong understanding of reliability, scalability, and performance in production
  • Experience with structured data modeling and validation
  • Ability to work independently and define technical scope
  • Clear communication skills with engineering and product teams

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.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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