Senior AI Architect for GenAI & Agent Platforms

Accenture; Raleigh (NC); On-site; USD 150,000 - 190,000; Full time

Job summary

Accenture seeks an AI/ML Senior Architect to deliver full-stack AI architecture across public, private, or sovereign clouds. You will design enterprise-grade agent frameworks with GenAI, foundation models, and knowledge engineering to solve complex business problems at scale.

You will lead end-to-end architecture, agent orchestration, governance, security, and MLOps pipelines while guiding engineering teams from ideation through production deployment across diverse client engagements.

Qualifications

• Bachelor’s degree or equivalent work experience.
• 12+ years of software experience in Python/Java and strong observability skills.
• 6+ years with AI technologies from public clouds and open source.

Responsibilities

• Architect enterprise-grade AI agent systems across public, private, and sovereign clouds.
• Lead AI strategy discussions, define reference architectures, and deliver agent frameworks.
• Oversee AgentOps/LLMOps, governance, security, and observability for scalable AI platforms.
• Evaluate technologies, build financial models, and drive TCO for AI solutions.
• Design multi-agent architectures with security, runtime, and knowledge layers.
• Collaborate with clients and Accenture teams to deliver end-to-end AI solutions.
• Architect and scale Generative AI platforms used by multiple AI solutions.
• Triage performance, cost, reliability, and trust in AI systems.

Skills

Python

Java

Observability

Education

Bachelor's degree or equivalent

Tools

Claude

LangGraph

CrewAI

AutoGen

Bedrock AgentCore

Anthropic Claude Agent SDK

Job description

Accenture seeks an AI/ML Senior Architect to deliver full-stack AI architecture across public, private, or sovereign clouds. You will design enterprise-grade agent frameworks with GenAI, foundation models, and knowledge engineering to solve complex business problems at scale.

You will lead end-to-end architecture, agent orchestration, governance, security, and MLOps pipelines while guiding engineering teams from ideation through production deployment across diverse client engagements.