AI Architect - FDE Associate Director

Information Technology Senior Management Forum

New York (NY)

On-site

USD 160,000 - 230,000

Full time

14 days+
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Job summary

Accenture is seeking an AI/ML Senior Architect to design and scale enterprise-grade Agentic AI platforms across public, private, or sovereign clouds. You will partner with clients to define AI strategy and architect reference solutions, leveraging GenAI, foundation models, and knowledge engineering to solve complex business problems at scale.

Lead end-to-end architecture across agent orchestration, governance, security, and observability while guiding engineering teams from ideation through

Responsibilities

  • Architect enterprise-ready AI agent systems: retrieval, orchestration, governance, evaluation, lifecycle observability.
  • Lead architecture workshops with client and Accenture teams; finalize requirements and TCO for AI solutions.
  • Evaluate, rationalize, and select technologies for full-stack AI platforms; build financial-viability models.
  • Design architectural blueprints (multi-agent, AI security, runtime, governance, DevOps, knowledge and data layer).
  • Design knowledge architecture (knowledge graphs, semantic layers) that enables AI agents at enterprise scale.
  • Architect for scalability, security, governance, and performance on public, private, and sovereign clouds.
  • Design reusable AI components, agents,

Job description

We Are:

The AWS Practice is home to our deepest AWS experts and supports Accenture's more than 1,500 certified AWS architects across the company. Join our team and be among Accenture's most talented AWS practitioners, our AWS SWAT team. The group is responsible for Accenture's most complex AWS projects and provides our delivery capability for the Accenture AWS Business Group (AABG). AABG is the deepest relationship Amazon Web Services has with any partner in the ecosystem. Choosing Accenture and the AWS Practice will take your AWS experience and skills to the next level and allow you to work in an innovative and collaborative environment. At Accenture, you can lead the world's largest enterprises on the path to native cloud transformation and serverless, on the leading edge of cloud.

Join Accenture and help transform leading organizations and communities around the world. The sheer scale of our capabilities and client engagements and the way we collaborate, operate and deliver value provides an unparalleled opportunity to grow and advance. Choose Accenture and make delivering innovative work part of your extraordinary career.

Learn more about our AABG and AWS at Accenture here:

https://www.accenture.com/us-en/service-aws-cloud

You Are:

An AI/ML Sr Architect delivering full-stack AI architecture on public, private, or sovereign clouds. You architect enterprise-grade platforms using AI Agents, Generative AI, Foundation Models, and Knowledge & Data Engineering to solve complex business problems at scale.

The Work:

The AI/ML Senior Architect is responsible for designing and scaling enterprise-grade Agentic AI platforms across public, private, and sovereign cloud environments. Partners with clients to define AI strategy, architect reference solutions, and deliver AI agent frameworks leveraging GenAI, foundation models, knowledge engineering, and cloud-native AI services. Leads end-to-end architecture covering agent orchestration, governance, security, AgentOps/LLMOps, observability, and scalable knowledge architectures, while guiding engineering teams from ideation through production deployment Generative AI platforms and frameworks used by multiple AI solutions.

Responsibilities:
  • Architect enterprise-ready AI agent systems: retrieval, orchestration, governance, evaluation, lifecycle observability.
  • Lead architecture workshops with client and Accenture teams; finalize requirements and TCO for AI solutions.
  • Evaluate, rationalize, and select technologies for full-stack AI platforms; build financial-viability models.
  • Design architectural blueprints (multi-agent, AI security, runtime, governance, DevOps, knowledge and data layer).
  • Design knowledge architecture (knowledge graphs, semantic layers) that enables AI agents at enterprise scale.
  • Architect for scalability, security, governance, and performance on public, private, and sovereign clouds.
  • Design reusable AI components, agents,
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