
Pioneering accelerated computing and AI
Senior Staff Software Engineer - AI Agent Platform at NVIDIA
About the role
We are looking for a Sr. Engineer to design, build, and scale the infrastructure powering NVIDIA’s AI agent ecosystem. You will work at the intersection of distributed systems, developer platforms, and agentic AI — building the foundational services that enable teams across the company to develop, deploy, orchestrate, and operate autonomous AI agents at production scale.
What you will be doing:
-
Build and develop platform services that own the full agent lifecycle from registration through deployment, execution, and teardown
-
Architect Kubernetes-based execution environments with pod lifecycle management, namespace isolation, persistent storage, and identity propagation
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Develop and maintain automated CI/CD pipelines using GitLab CI and ArgoCD, including reusable pipeline templates and deployment blueprints that standardize how agents are built across teams
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Build framework-agnostic infrastructure supporting multiple agent SDKs (Claude Code, OpenAI Codex, Lang Graph), with hands-on experience using harnesses, lifecycle hooks, skills configurability, observability (OTEL), and memory services
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Build and operate Kafka-based message pipelines and real-time event streaming using Redis Pub Sub and SSE
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Develop data ingestion pipelines, access interfaces, and storage layers that power AI agent knowledge and context
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Implement session management for state persistence, conversation history, and agent recovery across sessions
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Develop multi-layer auth using OAuth 2.0, JWT validation, token exchange, and gateway integration, and manage secrets lifecycle with Vault (provisioning, rotation, container injection)
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Partner with security teams on compliance, access controls, and approval workflows for agent operations
What we need to see:
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Bachelor's or Master's degree in Computer Science, Engineering, or related field (or equivalent experience), with 12+ years in software engineering — ideally in platform engineering, infrastructure, or developer tools
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Experience building and scaling AI agents in production using frameworks like Claude Code, Codex, or Lang Graph
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Deep Kubernetes expertise including pod orchestration, persistent storage, RBAC, and multi-cluster management
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Strong Python skills with production API experience using FastAPI, Flask, or similar async frameworks
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Proven track record designing distributed systems with Kafka, Redis, and Mongo
DB or PostgreSQL:
- Expertise building and managing robust CI/CD pipelines using Git
Lab CI and ArgoCD for continuous delivery to Kubernetes:
-
Experience designing AI data platform components (ingestion pipelines, vector stores, retrieval APIs, data preprocessing workflows) and building developer-facing platform APIs consumed by multiple engineering teams
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Solid grasp of auth and identity: OAuth 2.0, JWT, token exchange, and secrets management with Vault
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History of leading sophisticated technical projects such as migrations or greenfield platform builds, with strong interpersonal skills to drive alignment across teams and write clear design documents
Ways to stand out from the crowd:
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Experience building or operating AI agent platforms or agentic workflow systems, with hands-on expertise in agent protocols and frameworks like MCP, A2A, Lang Chain, or Lang Graph
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Hands-on experience with RAG architectures, embedding pipelines, and vector databases (Milvus, Pinecone, or Weaviate)
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Full-stack skills with React or Vue for building developer portals and dashboards
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Contributions to open-source infrastructure or platform tooling
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 200,000 USD - 322,000 USD for Level 5, and 248,000 USD - 391,000 USD for Level 6.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 9, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
Required skills
Distributed systems
Kubernetes
CI/CD
Kafka
OAuth 2.0
JWT
Platform engineering
Agent infrastructure
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About NVIDIA

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
Employees
Santa Clara
Headquarters
$4.57T
Valuation
Reviews
10 reviews
4.4
10 reviews
Work-life balance
2.8
Compensation
4.5
Culture
4.2
Career
4.3
Management
3.8
78%
Recommend to a friend
Pros
Cutting-edge technology and innovation
Excellent compensation and benefits
Great team culture and collaboration
Cons
High pressure and expectations
Poor work-life balance and long hours
Fast-paced environment leading to burnout
Salary Ranges
79 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
7 reports
$170,275
total per year
Base
$130,981
Stock
-
Bonus
-
$155,480
$234,166
Interview experience
5 interviews
Difficulty
3.0
/ 5
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
Latest updates
Negotiating NVIDIA's Offer
Base, stock, and sign-on negotiable. Recruiters invested in closing candidates. CEO reviews all 42K employee salaries monthly. Stock growth has made many employees millionaires.
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NVIDIA Company Reviews
WLB rated 3.9/5 (lowest category). 64% satisfied with WLB but 53% feel burnt out. Compensation rated 4.4-4.5/5. Experience highly team-dependent.
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NVIDIA Interview Discussions
Technical bar is high with 4-6 rounds. Process takes 4-8 weeks. Expect C++ questions, LeetCode medium, and system design. Difficulty rated 3.16/5.
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NVIDIA Culture Discussions
Team-dependent experience; sink-or-swim culture that rewards high performers but can be overwhelming. No politics, flat structure, but demanding workload with some teams requiring evening/weekend work.
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