Senior Staff Software Engineer - AI Agent Platform

Details

Design, build, and scale the infrastructure powering NVIDIA’s AI agent ecosystem. This role operates at the intersection of distributed systems, developer platforms, and agentic AI, building foundational services that enable teams across the company to develop, deploy, orchestrate, and operate autonomous AI agents at production scale.

Responsibilities

• Build platform services that manage the full agent lifecycle, from registration through deployment, execution, and teardown.
• Architect multi-tenant Kubernetes execution environments with pod lifecycle management, per-tenant namespace isolation, persistent storage, admission policy enforcement, and identity propagation.
• Develop and maintain automated CI/CD pipelines using GitLab CI and ArgoCD, including reusable pipeline templates and deployment blueprints.
• Build framework-agnostic infrastructure supporting multiple agent SDKs and harnesses, including lifecycle hooks, skills configuration, memory services, and OpenTelemetry instrumentation.
• Build and operate Kafka-based message pipelines and real-time event streaming using Redis Pub/Sub and server-sent events (SSE).
• Develop data ingestion pipelines, access interfaces, and storage layers for AI agent knowledge and context.
• Implement session management for state persistence, conversation history, and agent recovery across sessions.
• Develop multi-layer authentication using OAuth 2.0, JWT validation, token exchange, and gateway integration.
• Manage the secrets lifecycle with Vault, including provisioning, rotation, and container injection.
• Partner with security teams on compliance, access controls, and approval workflows for agent operations.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• 12+ years of software engineering experience, ideally in platform engineering, infrastructure, or developer tools.
• Experience building and scaling AI agents in production using frameworks such as Claude Code, Codex, or LangGraph.
• Deep Kubernetes expertise, including pod orchestration, persistent storage, RBAC, and multi-cluster management.
• Strong Python skills and production API experience using FastAPI, Flask, or similar asynchronous frameworks.
• Proven experience designing distributed systems with Kafka, Redis, and MongoDB or PostgreSQL.
• Expertise building and managing CI/CD pipelines with GitLab CI and ArgoCD for continuous delivery to Kubernetes.
• Experience designing AI data platform components, including ingestion pipelines, vector stores, retrieval APIs, and data preprocessing workflows.
• Experience building developer-facing platform APIs consumed by multiple engineering teams.
• Knowledge of OAuth 2.0, JWT, token exchange, identity, and secrets management with Vault.
• Experience leading sophisticated technical projects, such as migrations or greenfield platform builds.
• Strong interpersonal skills for driving alignment across teams and writing clear design documents.

Additional Qualifications

• Experience building or operating AI agent platforms or agentic workflow systems.
• Hands-on expertise with agent protocols and frameworks such as MCP, A2A, LangChain, or LangGraph.
• Experience with RAG architectures, embedding pipelines, and vector databases such as Milvus, Pinecone, or Weaviate.
• Full-stack skills with React or Vue for building developer portals and dashboards.
• Contributions to open-source infrastructure or platform tooling.

Compensation and Benefits

• Base salary range: $200,000–$322,000 for Level 5.
• Base salary range: $248,000–$391,000 for Level 6.
• Salary is determined based on location, experience, and the pay of employees in similar positions.
• Eligible for equity and benefits.
• Applications will be accepted at least until October 20, 2026.
• NVIDIA is an equal opportunity employer committed to an inclusive work environment.