AI Workflow Architect - Enterprise Cloud-Native

General Motors; Mountain View (CA); On-site; USD 202,000 - 310,000; Full time

Job summary

General Motors is seeking an experienced engineer to own end-to-end AI workflow transformations across GM platforms. You will design secure, reusable enterprise-grade AI solutions that modernize how work gets done, partnering with engineering, product, and business teams to scale adoption and governance.

You will build and operate cloud-native backend services, implement HITL validation, and drive robust testing, release processes, and secure integrations.

Qualifications

• 10+ years of hands-on software engineering or platform architecture in enterprise environments.
• Proven experience with GCP-based transformations and secure, scalable AI solutions.
• Strong background modernizing workflows and integrating with enterprise systems.
• Degree or equivalent practical experience in a technical field.

Responsibilities

• Own end-to-end AI workflow transformations from intake to governance.
• Design secure, enterprise-grade AI solutions across GM platforms.
• Build and operate cloud-native backend services in Python/Node.js.
• Develop testing, CI/CD, and release environments with GitHub.
• Architect multi-step agents, HITL validation, and guardrails for production.

Skills

Python

JavaScript

Node.js

TypeScript

GCP

Vertex AI

Gemini

AI/ML Systems

CI/CD

Security & IAM

REST APIs

HITL

GitHub

Education

Bachelor's degree in Computer Science or related field

Tools

Cloud Run

Pub/Sub

Cloud Functions

API Gateway

OAuth2

IAM

LangChain

LlamaIndex

Vertex AI

Job description

General Motors is seeking an experienced engineer to own end-to-end AI workflow transformations across GM platforms. You will design secure, reusable enterprise-grade AI solutions that modernize how work gets done, partnering with engineering, product, and business teams to scale adoption and governance.

You will build and operate cloud-native backend services, implement HITL validation, and drive robust testing, release processes, and secure integrations.