# Forward Deployed Engineer - Finance at NVIDIA

NVIDIA is hiring a Forward Deployed Engineer - Finance in Santa Clara, United States. It pays $116k-$184k a year and Level rates it Works on AI ●●●○; you can [apply on NVIDIA](https://jobsbylevel.com/go/5f2909c8-1a80-4eec-9ee3-26ab71a98bec?utm_medium=ai-agent).

AI Level 3, AI centrality 63 out of 100. US, CA, Santa Clara.

## Details

- Company: [NVIDIA](https://jobsbylevel.com/companies/nvidia)
- AI level: AI Level 3 (score 63 out of 100)
- Location: US, CA, Santa Clara
- Salary: $116k-$184k
- Posted: October 28, 2026
- Apply: https://jobsbylevel.com/go/5f2909c8-1a80-4eec-9ee3-26ab71a98bec?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=forward-deployed-engineer-finance-at-nvidia-b8e1b5

## Prepare for this job

The job page lists 5 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/forward-deployed-engineer-finance-at-nvidia-b8e1b5

## Description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA Finance is hiring a Forward Deployed Engineer and AI Enabling expert to help turn that potential into measurable business outcomes. Embedded within the Finance AI team, you will work at the intersection of a high variety of finance functions at NVIDIA, data platform teams, and applied AI. You will partner with finance leaders, subject-matter experts, data scientists, data engineers, DevOps engineers, AI citizen developers, knowledge workers, and external vendors to discover high-value opportunities, build trusted solutions, and help teams adopt new ways of working. This is a hands-on role for someone who can move comfortably from an ambiguous business problem to a working prototype, a production-ready solution, and sustained adoption. You will combine technical depth, business-savvy thinking, program leadership, and a strong teaching capacity to enable AI across our Finance organization. What you’ll be doing: Translate complex finance workflows and ambiguous business problems into clear requirements, technical designs, success measures, and delivery plans — guiding architecture across data, models, APIs, orchestration, UX, and human-in-the-loop controls. Prototype and productionize AI solutions: agents, retrieval-augmented generation, workflow automation, analytics, and ML applications. Partner with data owners and platform teams to securely integrate structured and unstructured data, set access controls, and improve data quality and lineage. Lead technically and organizationally complex initiatives from discovery to launch, balancing experimentation with enterprise scale, security, governance, and maintainability. Build reusable reference architectures, patterns, and enablement assets, and communicate recommendations, tradeoffs, and results to audiences from finance operators to executives and engineers. What we need to see: Hands-on Python, SQL, and Git, with Databricks or a comparable cloud data and AI platform. Practical experience building and deploying modern AI — LLMs, prompt/context design, agents, MCPs, and evaluations — and integrating applications via APIs across structured and unstructured data. Strong product and program judgment: create clarity from ambiguity, define an MVP, manage dependencies and risk, and deliver iteratively. Working knowledge of responsible AI, privacy, security, and governance, with excellent communication that teaches technical concepts to nontechnical audiences and influences across functions without formal authority. 3+ years in computer science, data science/engineering, analytics, automation, or applied AI. A BS or MS degree in Data Science, Computer Science, Engineering, Economics, Finance, Business Analytics, or a related field, or equivalent experience. Ways to stand out from the crowd: Applied AI, automation, or advanced analytics to tax, corporate development, treasury, venture capital, financial services, procurement, audit, or related areas. Designed agentic workflows and securely connected models to enterprise systems like SAP, SFDC, or Workday. Built communities of practice and taught varied technical audiences, using feedback and adoption data to improve enablement. Experience in a large, global technology company or another complex, high-growth environment. A collaborative,

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