Senior Staff Engineer, Enterprise SaaS Platform and Automation
at Nvidia
USD 168,000-322,000 per year
Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 4
Python @ 7
Hiring @ 4
Slack @ 4
API @ 7
OAuth @ 4
LLM @ 4
Microsoft 365 @ 4
Compliance @ 4
Observability @ 4
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today the company is tapping into the potential of AI to define the next era of computing. This role sits at the inflection point of how enterprise work gets done: building automation and agentic systems that replace repetitive human work and owning engineering behind SaaS onboarding, support automation, vendor integration, and employee productivity tooling across platforms like Microsoft 365, Slack, and Glean.
Responsibilities
- Design and build agentic systems that automate the full SaaS application lifecycle — onboarding, provisioning, support triage, offboarding — eliminating manual processes across the IT SaaS portfolio.
- Architect and implement automation and integration solutions across Microsoft 365, Slack, Glean, and other enterprise SaaS platforms; define integration patterns and engineering standards for the team.
- Build AI-powered support automation: intelligent triage, self-healing workflows, proactive issue detection that reduce human intervention and improve employee experience at scale.
- Engineer vendor integration frameworks that automate data flows, contract triggers, and operational touchpoints between NVIDIA systems and SaaS vendors.
- Develop and deploy MCP-based integrations and AI agent pipelines that surface insights, automate decisions, and enable employees to be more productive.
- Instrument platforms for observability: build dashboards, alerts, and analytics for real-time visibility into SaaS health, adoption, and cost.
- Partner with security and compliance teams to ensure automated workflows meet enterprise standards; build guardrails into automation.
- Mentor engineers and establish engineering best practices — code reviews, runbooks, testing frameworks — for building and operating systems.
Requirements
- Bachelor's or Master's degree in Computer Science, Computer Engineering, or related field (or equivalent experience).
- 8+ years of engineering experience building production-grade automation systems, integrations, or platforms at enterprise scale.
- Strong software engineering fundamentals: Python, APIs, event-driven architectures, workflow orchestration, with an instinct to build rather than just configure.
- Hands-on experience with AI/ML frameworks, LLMs, or agentic systems and demonstrated ability to apply AI to operational problems.
- Deep familiarity with enterprise SaaS platforms (Microsoft 365, Slack, or similar) and the integration patterns, APIs, and data models that underpin them.
- Strong systems thinking: ability to design durable solutions and anticipate failure modes.
- Clear communicator who can translate engineering decisions into business outcomes for non-technical stakeholders.
Ways to Stand Out
- Experience building MCP servers, AI agents, or LLM-powered workflows in production.
- Track record of measurably reducing manual IT or operations work through automation (quantified results).
- Experience with SaaS vendor management, contract integrations, or procurement automation.
- Passion for employee productivity and building tools used daily by real people.
- Knowledge of enterprise security and compliance requirements for SaaS integrations (OAuth, SCIM, SSO, data residency).
Compensation & Benefits
- Base salary ranges (location- and level-dependent):
- Level 4: 168,000 USD - 270,250 USD
- Level 5: 200,000 USD - 322,000 USD
- Eligible for equity and company benefits (link to NVIDIA benefits referenced in posting).
Additional Information
- Applications accepted at least until May 25, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and values diversity in hiring and promotion practices.