Senior Software Engineer, Agentic Systems

This is a fully remote position, open to applicants in California, +4 more states.

📋 Description

• Design and develop APIs that prioritize Python, along with SDK workflows and plugin interfaces aimed at building, assessing, and enhancing agents across various runtimes and product surfaces.

• Create reusable systems to observe behavior, evaluate progress, identify regressions, and transform runtime data into actionable product decisions.

• Develop systems for collecting, normalizing, validating, and analyzing both agent execution data and evaluation datasets.

• Collaborate with research, product, platform, and infrastructure teams to seamlessly integrate agentic capabilities across NVIDIA agent runtimes and developer workflows.

• Assist in transforming emerging techniques for agent development and enhancement into dependable, reusable product features.

• Enhance reliability, observability, debuggability, and overall performance across NeMoStack services, SDKs, plugins, jobs, and developer workflows.

• Establish robust test coverage across unit, integration, E2E, Docker, and Kubernetes workflows.

• Champion 'speed of light' engineering principles: rapid iteration, high ownership, pragmatic decision-making, and performance-focused implementation within production constraints.

• Offer senior technical leadership through design reviews, code reviews, mentoring, and tackling ambiguous cross-component challenges.

⛳️ Requirements

• Bachelor's, Master's, or equivalent experience in Computer Science, Computer Engineering, or a related technical discipline.

• Over 5 years of professional software engineering experience in building production systems.

• Exceptional Python engineering expertise, which includes API design, typing, testing, debugging, performance evaluation, and sustainable software design.

• Experience in designing SDKs, libraries, plugins, CLIs, or other developer-facing interfaces.

• Familiarity with distributed systems, cloud-native services, containers, Kubernetes, or job orchestration.

• Strong grasp of reliability, scalability, security, and performance trade-offs in production infrastructure.

• Experience with structured data modeling and validation systems like Pydantic, typed schemas, event/trace models, or SDK-generated types.

• Capability to work autonomously, define technical scope, decompose ambiguous problems, and drive initiatives across team boundaries.

• Strong communication skills and a proven history of collaborating with engineering, product, research, or customer-facing teams.

🏝️ Benefits

• Equity

• Benefits