Finance AI Engineering Manager: Lead & Deliver AI Solutions

NVIDIA Corporation; Santa Clara (CA); On-site; USD 168,000 - 322,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation in Santa Clara, CA seeks an AI Engineering Manager to lead a Finance AI team building AI solutions for finance operations. You will partner across FP&A, accounting, treasury, tax and procurement, and stay hands-on reviewing designs and code while guiding the technical strategy and vendor evaluations.

The role requires extensive experience leading engineering teams, deep AI system knowledge, and a track record delivering real business value in data-rich environments.

Qualifications

• Experience leading engineering teams that ship production software.
• Hands-on depth building AI systems and fluency in data and system architecture.
• Track record delivering technology to address real business problems in data-rich domains.

Responsibilities

• Partner with the CFO org (FP&A, Accounting, Treasury, Tax, Procurement) to identify high-value problems and turn them into AI applications, agents, and automation.
• Set the technical direction and quality bar for Finance AI, adopting emerging technologies where appropriate.
• Review designs and code, make hard technical calls, and set engineering quality standards for agents, pipelines, and model integrations.
• Lead the end-to-end evaluation of external AI vendors: define criteria, run POCs, and compare build vs buy options.
• Scale the team’s output as AI adoption grows across Finance with reusable components and patterns.

Skills

Engineering leadership

Hands-on AI

Technical delivery

Education

BSc/MSc in CS/Engineering/Data Science or equivalent

Job description

NVIDIA Corporation in Santa Clara, CA seeks an AI Engineering Manager to lead a Finance AI team building AI solutions for finance operations. You will partner across FP&A, accounting, treasury, tax and procurement, and stay hands-on reviewing designs and code while guiding the technical strategy and vendor evaluations.

The role requires extensive experience leading engineering teams, deep AI system knowledge, and a track record delivering real business value in data-rich environments.