Principal AI Workflow Engineer

Nvidia

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $248,000–$391,000 / yr
Posted: 3 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $220k

This role $320k

$137k most similar roles pay here $418k

This role pays more than 92% of similar roles. Most pay $193,075–$247,075 — the shaded band above. At the midpoint, this role pays about $320k versus about $220k for comparable roles.

Based on 239 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 899 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 886 roles with salary data.

Most-posted roles

View all roles at Nvidia

At a glance

TL;DR · Principal AI Workflow Engineer

Role Posting Log in to save

The Principal AI Workflow Engineer joins the Enterprise Integration and API Team to develop, maintain, and architect innovative software solutions at the forefront of AI-augmented engineering. You will build a developer-centric Unified Integration Framework, creating high-throughput, real-time integration platforms using event-driven and asynchronous orchestration patterns. The role involves embedding agentic AI capabilities into enterprise systems to create autonomous, self-healing workflows for complex business processes across multi-cloud environments. Key technologies include Codex, Claude Code, n8n, and SAP Integration Suite tools like CPI and API-M. You will work with REST, GraphQL, SOAP, and various programming languages including Java, Groovy, Python, and PowerShell. The position addresses the challenge of creating secure, scalable connectivity across heterogeneous systems while managing complex EDI deployments and identity management protocols to support large-scale distributed infrastructure and automated integration lifecycles.

Skills

SAP Integration Suite CPI n8n Codex Claude Code Python Java Groovy PowerShell REST GraphQL SOAP Event Driven Architecture Microservices CI/CD Git Jenkins JFrog Datadog Splunk EDI SAML JWT

What you'll do

Develop the roadmap and framework for enterprise integration, B2B, and API ecosystems using agentic AI capabilities.
Architect high-throughput, real-time integration platforms using event-driven and AI-augmented orchestration patterns.
Design context-aware integration solutions for complex business processes across multi-cloud environments and various software systems.
Implement intelligent algorithms and autonomous workflows into production-grade integration systems.
Orchestrate autonomous, closed-loop integration lifecycles featuring self-monitoring, self-healing, and proactive alerting.
Build a developer-centric Unified Integration Framework to enable secure, self-service connectivity across applications.
Manage the full API lifecycle including design, construction, governance, and intelligent routing.
Integrate agentic workflows into integration pipelines using tools like Codex, Claude Code, and n8n.

What we're looking for

Bachelor’s/Master’s degree or equivalent experience in Computer Science or a related Engineering degree.
15+ years of proven experience in enterprise integration.
Expertise in microservices, integration patterns, and reusable frameworks across heterogeneous systems and partner ecosystems.
Experience with SAP Integration Suite (CPI, API-M, TPM) and AI coding assistants like Codex and Claude Code.
Proficiency in integrating distributed systems using REST, GraphQL, SOAP, and Event Driven Architecture.
Strong programming and scripting skills in Java, Groovy, Python, and PowerShell.
Expertise in identity management, access control (SAML, JWT, Certificates), and CI/CD pipelines (Git, Jenkins, JFrog).
Experience building AI-first, agentic integration architectures across SAP and non-SAP ecosystems (preferred).

Save