NVIDIA
Technology
SeniorSoftwareEngineer,AgenticSystems
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“Senior Software Engineer, Agentic Systems at NVIDIA. Skills: Python, Agentic Systems, AI Systems, Software Engineering. Design and implement Python-first APIs. Develop SDK workflows”
What You'll Achieve.
make empirically grounded improvements over time; turning runtime evidence into product decisions; improve reliability; improve observability; improve debuggability; improve performance; measure and improve real product outcomes; connect technical evaluation work to business outcomes
Industry & Context.
break down ambiguous problems; ownership of ambiguous cross-component problems
What They're Looking For.
Must Have
5+ years of professional software engineering experience building production systems, Excellent Python engineering skills, API design, typing, testing, debugging, performance analysis, maintainable software design, Experience designing SDKs, libraries, plugins, CLIs, or other developer-facing interfaces, Experience with distributed systems, cloud-native services, containers, Kubernetes, job orchestration, understanding of reliability, scalability, security, and performance tradeoffs in production infrastructure, Experience with structured data modeling and validation systems, Pydantic, typed schemas, event/trace models, SDK-generated types, Ability to work independently, define technical scope, break down ambiguous problems, drive work across team boundaries, Clear communication skills, track record of collaborating with engineering, product, research, or customer-facing teams
Nice to Have
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, tool-using agents, RAG agents, workflow agents, coding agents, long-running autonomous systems, Experience integrating evaluation capabilities across multiple products, runtimes, or internal platforms, Python SDKs, plugins, shared developer tooling, ability to connect technical evaluation work to business outcomes, product quality, user experience, reliability, operational efficiency, Experience with enterprise AI systems where measurement, regression testing, observability, governance, and continuous improvement are required for production deployment
What You'll Do.
Design and implement Python-first APIs
Develop SDK workflows
Build plugin interfaces
Measure and improve agents
Build reusable systems for observing behavior
and analyze agent execution data
Integrate agentic capabilities
Turn techniques into product capabilities
Improve observability
Improve debuggability
Provide senior technical leadership
Conduct design reviews
Own ambiguous cross-component problems
How You'll Work.
Team & Collaboration
Partner with research teams; Partner with product teams; Partner with platform teams; Partner with infrastructure teams; Collaborate with engineering teams; Collaborate with product teams; Collaborate with research teams; Collaborate with customer-facing teams
Communication Scope
Clear communication skills
Process & Methodology
define technical scope, break down ambiguous problems, drive work across team boundaries
Full Job Description
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 pr
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