AI Architect - FDE Associate Director

Technology Architecture Associate Manager Mid-Level Full time Job No. R00353640 Multiple Locations

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, and solution patterns for repeatable engagement delivery.
• Architect and stand up custom agent frameworks across providers (Amazon Bedrock AgentCore, Anthropic Claude Agent SDK); design reference architectures that scale across engagements.
• Run AgentOps, LLMOps, AI Governance, AI Security, and Observability; drive MLOps pipelines for ML and LLM lifecycle.
• Troubleshoot, optimize, and tune AI systems for performance, cost, reliability, and trust.

Travel may be required for this role. The amount of travel will vary from 25% to 100% depending on business need and client requirements.

Here’s What You Need:

• Minimum of 12 years of experience in Python, Java, or equivalent. Comfortable with evaluation tooling, logging, monitoring, and observability.
• Minimum of 6 years of experience with key AI technologies from public cloud providers, open source, and 3rd party tooling.
• Minimum of 4 years experience in designing, engineering, and operationalizing large-scale AI/ML solutions on at least one major public cloud, using cloud-native AI services and frameworks, open-source technologies, and 3rd party tools.

• Minimum of 2 years of experience in the following:

  • Hands-on experience with AI platforms (Claude, open-source), agentic orchestration tools (LangGraph, CrewAI, AutoGen), and MLOps/LLMOps practices across the ML and LLM lifecycle.
  • Designing and implementing scaled Agentic AI a…