Senior Software Engineer
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; partner with research, product, platform, and infrastructure teams to integrate agentic capabilities broadly across NVIDIA agent runtimes and developer workflows; provide senior technical leadership through design reviews, code reviews, mentoring, and ownership of ambiguous cross-component problems.
- Santa Clara, California, United States
- $184K–$357K per year
- Posted Nov 6, 2026
Responsibilities
- Design and implement Python-first APIs, SDK workflows, and plugin interfaces
- Build reusable systems for observing behavior, measuring progress, detecting regressions
- 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
- Help turn emerging agent development and improvement techniques into reliable, reusable product capabilities
- Improve reliability, observability, debuggability, and performance across NeMo Platform, 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
Requirements
- BS, MS, or equivalent experience in Computer Science, Computer Engineering, or a related technical field
- Experience in a AI systems
- Experience in a agentic development
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, 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
Skills
Benefits
- equity and benefits
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