Senior Manager, Engineering - Enterprise AI and Automation
Company websitenvidia.com (NVIDIA, opens in new tab)
Base salary $272,000 to $431,250
Employer-published annual base salary, USD. Advertised base range in Santa Clara, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSanta Clara, CA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (1 h ago) · observed since
About this job
As a Senior Engineering Manager for Agentic Systems & Platform Architecture, you will lead the strategy and execution for NVIDIA’s agentic developer platform—deeply understanding how teams across the company build, evaluate, and improve autonomous agents, and turning those evolving patterns into scalable platform capabilities. You will identify gaps and friction, drive rapid proof-of-concepts on emerging agent constructs and ecosystem tools, and operationalize the best approaches into reusable building blocks, integrations, and governance mechanisms that accelerate developer productivity and agent quality. If you’re passionate about staying at the forefront of agent architectures and turning experimentation into real business impact, this role offers a chance to build a platform. This platform helps teams safely ship more autonomous systems at NVIDIA scale.
What you will be doing:
Track and deeply understand evolving agent development patterns across NVIDIA and the broader ecosystem
Identify gaps and friction in current agent architectures, and translate insights into a platform strategy that boosts developer velocity and agent quality—backed by evaluations, benchmarking, and feedback loops
Assess and integrate open source and third-party tools where they add leverage; drive clear build-vs-use decisions
Architect and integrate high-performance data pipelines, RAG systems, vector databases, and GPU-optimized training and inference workflows.
Lead integration of the AI Data Platform into NVIDIA’s on-prem AI Factory, optimizing GPU-to-storage throughput, data locality, and distributed inference performance.
Establish and enforce robust Agent Governance policies across the platform, covering model/tool usage, data lineage, and ensuring adherence to compliance and Responsible AI frameworks.
Design, implement, and maintain a centralized Agent Safety Toolkit, providing developers with pre-vetted components for input/output guardrails and prompt injection defenses
Lead and grow a high-performing team along with a multi-functional community to standardize procedures and scale adoption
What we need to see:
Bachelor’s degree in CS/Engineering or equivalent experience
10+ overall years in software engineering, including 4+ years managing high-performing teams
Strong hands-on experience with evolving agent architectures and open-source libraries; deep expertise in LLM/agent architectures—leading POCs and integrating them into real business use cases with measurable adoption/impact
Ability to turn fast-moving, ambiguous problem spaces into clear platform strategy, roadmap, and outcomes
Proven track record building multi-team developer platforms (APIs/SDKs, reusable components, reference implementations)
Experience building evaluation/benchmarking systems for agent workflows (metrics, regression, feedback loops)
Strong judgment integrating OSS/3P tools; clear build-vs-use decision-making and integration strategy
Product approach for safety and governance: controls, audit ability, monitoring, and risk management
Strong leadership and executive communication (engineering, product, security, research)
Ways to stand out from the crowd:
Experience implementing enterprise-grade governance for agent systems (controls, audit-ability, monitoring, policy enforcement) in production autonomous workflows
Demonstrated wins taking new/open-source agent constructs from POC to production adoption, with clear business impact (cycle time, quality, cost, reliability)
Built and scaled an agent platform or agent developer experience used by multiple teams (SDKs, templates, reference apps, reusable building blocks)
Clear point of view and real examples on build-vs-use decisions—when to adopt OSS/3P vs build internal primitives—and how to operationalize the choice
Deep experience with agent evaluation at scale (long-horizon tasks, tool correctness, reliability testing, automated regressions, offline/online feedback loops)
We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Ready to take your career to the next level? Apply now and join the innovation!
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.Source: NVIDIA on Workday · View original posting (opens in new tab)
Pay in context
This role's base floor ($272,000) is above 93% of the 5,063 Software Engineering roles in California listed on this site; 52 others list the same floor. Their median floor is $176,600; the middle half runs from $149,365 to $204,000.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 8, 2026.
This listingSenior Manager, Engineering - Enterprise AI and Automation$272,000 to $431,250
Senior Director, Procurement Operations and Systems$272K to $414K
Principal Research Scientist, Synthetic Data Generation$272,000 to $431,250
Senior Manager, AI and HPC Cluster Engineering Enablement$272,000 to $488,750
Senior Engineering Manager, Object Storage - DGX Cloud$272,000 to $431,250
Principal Systems Software Engineer$272,000 to $431,250
Senior Manager, Developer Infrastructure and Build Engineering$272,000 to $431,250
Chart as a table
| Role | Published base |
|---|---|
| Senior Manager, Engineering - Enterprise AI and Automation (this listing) | $272,000 - $431,250 |
| Senior Director, Procurement Operations and Systems | $272K - $414K |
| Principal Research Scientist, Synthetic Data Generation | $272,000 - $431,250 |
| Senior Manager, AI and HPC Cluster Engineering Enablement | $272,000 - $488,750 |
| Senior Engineering Manager, Object Storage - DGX Cloud | $272,000 - $431,250 |
| Principal Systems Software Engineer | $272,000 - $431,250 |
| Senior Manager, Developer Infrastructure and Build Engineering | $272,000 - $431,250 |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-10-30
Where this pay comes from
Location as the employer wrote it: US, CA, Santa Clara
base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
