Senior AI Platform Architect for Enterprise-Scale Gen AI

Accenture; Culver City (CA); On-site; USD 94,000 - 294,000; Full time

Job summary

Accenture in California is seeking an Advanced AI Architect to design and deliver full-stack AI platforms and solutions for enterprise-scale needs on public, private, or sovereign clouds. You will lead architecture workshops, define requirements, and create blueprints for multi-agent, AI security, governance, and DevOps across AI initiatives.

This high-impact role requires deep expertise in AI technologies, knowledge graphs, data engineering, and experience across large cloud environments, with

Qualifications

• Minimum of 5 years of experience designing, engineering & operationalizing large-scale AI/ML solutions on public cloud platforms.
• Minimum of 5 years of expert level understanding of key AI technologies from public cloud providers, open source and 3rd party technologies.
• Bachelor's degree or equivalent work experience (minimum 12 years).

Responsibilities

• Lead AI architecture and technical design workshops with client and Accenture teams.
• Design and document multi-agent, AI security, governance, and DevOps blueprints.
• Implement AgentOps / LLMOps, AI governance, AI security, and observability solutions.

Skills

AI architecture

Full stack AI design

AgentOps

LLMOps

AI governance

AI security

Knowledge & data engineering

Knowledge graphs

Semantic layers

Foundation models

Education

Bachelor's degree or equivalent

Tools

Public cloud platforms

Open-source tech

Third-party tools

Job description

Accenture in California is seeking an Advanced AI Architect to design and deliver full-stack AI platforms and solutions for enterprise-scale needs on public, private, or sovereign clouds. You will lead architecture workshops, define requirements, and create blueprints for multi-agent, AI security, governance, and DevOps across AI initiatives.

This high-impact role requires deep expertise in AI technologies, knowledge graphs, data engineering, and experience across large cloud environments, with