AI Platform Architect: Cloud Native, LLMs & Infra

GAC Solutions; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

GAC Solutions in Jersey City, NJ seeks a senior AI/ML architecture lead to drive scalable AI platform decisions across distributed teams. You will define standards for LLMs, model serving, RAG, embeddings, and AI infrastructure while coordinating with risk, security, and data groups.

You will shape Terraform/IaC practices, DevOps pipelines, and cloud-agnostic patterns, ensuring observability and resiliency across enterprise systems.

Qualifications

• 10+ years in AI/ML systems, distributed systems, enterprise architecture, or platform engineering.
• Deep experience with LLMs, RAG, embeddings, model serving, AI orchestration, evaluation frameworks, and AI infrastructure.
• Proven track record defining architecture and technical standards across multiple engineering teams.
• Strong AWS cloud architecture experience or comparable hyperscaler depth, with clear ability to design cloud-agnostic AI platform patterns.
• Experience shaping Terraform/IaC standards, DevOps pipelines, secure deployment patterns, observability, resiliency, and platform operating models.
• Ability to influence senior stakeholders and operate across business, technology, risk, compliance, security, data, and architecture forums.

Skills

AI/ML systems

Distributed systems

Enterprise architecture

Platform engineering

LLMs & RAG

Embeddings

Model serving

AI orchestration

Evaluation frameworks

AI infrastructure

Terraform/IaC

DevOps pipelines

Observability

Stakeholder influence

Job description

GAC Solutions in Jersey City, NJ seeks a senior AI/ML architecture lead to drive scalable AI platform decisions across distributed teams. You will define standards for LLMs, model serving, RAG, embeddings, and AI infrastructure while coordinating with risk, security, and data groups.

You will shape Terraform/IaC practices, DevOps pipelines, and cloud-agnostic patterns, ensuring observability and resiliency across enterprise systems.