Senior AI Platform Architect

Aimlroles; United States; On-site; USD 128,000 - 213,000; Full time

Benefits offered by this job

Medical, dental, vision

Company 401(k) with match

Tuition assistance

Paid holidays & parental leave

Job summary

GE Vernova seeks a Senior Staff AI Engineer to lead enterprise full-stack and AI platform architecture, shaping scalable microservices, REST APIs, and RAG-enabled multimodal features. You will own end-to-end technical decisions, balancing reliability, performance, and cloud costs.

Expect collaboration with teams, mentorship of engineers, and oversight of reviews and integrations to deliver measurable impact. The role emphasizes autonomy, agile practices, and observability for AI capabilities.

Qualifications

• Bachelor’s degree in computer science, computer engineering, or related field.
• 8+ years shipping production applications with LLMs or AI services at scale.
• Experience leading technical teams and guiding contractors or vendors.
• Strong cloud and containerization experience (AWS/GCP/Azure, Docker, Kubernetes).
• Experience with code review, QA methodologies, and technical oversight.

Responsibilities

• Identify and deliver reusable AI components for forward-deployed engineers.
• Ship resilient REST APIs and microservices.
• Build RAG and multimodal LLM features.
• Design agentic workflows for autonomous tasks.
• Mentor engineers and coordinate with contractors and partners.

Skills

Python

Java

Go

JavaScript/TypeScript

Cloud platforms

LLMs/AI services

Distributed systems

AI/ML architecture

Education

Bachelor’s degree in CS/CE or related field

Tools

Docker

Kubernetes

AWS/GCP/Azure

Job description

GE Vernova seeks a Senior Staff AI Engineer to lead enterprise full-stack and AI platform architecture, shaping scalable microservices, REST APIs, and RAG-enabled multimodal features. You will own end-to-end technical decisions, balancing reliability, performance, and cloud costs.

Expect collaboration with teams, mentorship of engineers, and oversight of reviews and integrations to deliver measurable impact. The role emphasizes autonomy, agile practices, and observability for AI capabilities.