招聘
必备技能
Python
What does it look like to build infrastructure that thinks — that triages failures, files bugs, and surfaces root causes without waiting for a human to ask? What if the tools we build today become the foundation for how the whole industry does software quality tomorrow? We are building an engineering team where a small group of high-agency engineers, equipped with well-designed autonomous agents, can accomplish what previously required a much larger organization. This role sits at the center of that transformation. You will design and build the agentic infrastructure that powers our test automation and quality engineering workflows for the NVIDIA Omniverse platform. This isn’t about using AI tools to work faster — it’s about building the infrastructure that other engineers depend on to ship high-quality software with greater speed and confidence!
What you’ll be doing:
As a Senior Tools Development Engineer on our team, you will own end-to-end outcomes, work with significant autonomy, and have a direct impact on the reliability of one of NVIDIA's most strategic developer platforms. In this role you can expect to:
Build Agentic Test Pipelines:
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Develop and deploy multi-agent systems for automated test generation, log analysis, failure triage, and bug-filing workflows
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Build and maintain agent orchestration frameworks using tools such as Claude Code, MCP servers, and agent SDK patterns
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Create autonomous pipelines that reduce cognitive load on engineers by routing failures, surfacing root causes, and generating actionable bug reports
Own Infrastructure Quality:
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Build evaluation systems to measure agent output quality — ensuring autonomous pipelines are reliable, not just fast
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Establish observability and monitoring for agentic workflows so failures are transparent, debug-gable, and recoverable
Drive Team Adoption:
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Build internal tooling that is adoptable, not just technically impressive — with clear documentation and low onboarding friction
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Collaborate with the broader QA team to identify automation opportunities and build the tools that accelerate them
What we need to see:
Core Technical Skills:
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Strong Python engineering — clean, testable, maintainable code with a systems-level perspective
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Deep familiarity with AI-native development workflows — Claude Code, Cursor, LLM APIs, prompt engineering in production
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Hands-on experience building multi-agent or autonomous systems that have shipped and run without continuous supervision
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Clear understanding of where LLMs fail — hallucination, context degradation, tool misuse — and experience building mitigations into system design, including evaluation frameworks for AI-generated outputs
Test & Quality Engineering Foundation:
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A graduate degree in Computer Science Engineering or equivalent
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5+ years in test automation, CI/CD pipeline design, or software quality engineering, including failure analysis and test triage at scale
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Ability to reason about test coverage strategically across a complex, frequently-releasing platform SDK
Mindset & Working Style:
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High agency — owns outcomes end-to-end, defines their own path in ambiguous problem spaces
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The patience and communication skill to build systems that colleagues can trust and adopt
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Intellectual honesty about where systems break, with a habit of building in recovery paths rather than hiding failures
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. Due to outstanding growth, our elite engineering teams are rapidly growing. If you're creative with a real passion for technology, we want to hear from you. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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关于NVIDIA

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
员工数
Santa Clara
总部位置
$4.57T
企业估值
评价
4.4
10条评价
工作生活平衡
2.8
薪酬
4.2
企业文化
4.3
职业发展
4.1
管理层
3.8
78%
推荐给朋友
优点
Cutting-edge technology and innovation
Excellent compensation and benefits
Great team culture and collaboration
缺点
Work-life balance challenges
High pressure and stress
Long hours required
薪资范围
67个数据点
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
7份报告
$170,275
年薪总额
基本工资
$130,981
股票
-
奖金
-
$155,480
$234,166
面试经验
5次面试
难度
3.0
/ 5
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
新闻动态
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 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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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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NaNw ago
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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