This role pays more than
81%
of similar roles. Most pay
$193,830–$270,244
— the shaded band above.
At the midpoint, this role pays about
$288k
versus about
$232k
for comparable roles.
Based on 240 similar postings.
Employer
About Accenture
Accenture is a leading global professional services company specializing in IT, strategy, consulting, and operations, with a strong focus on digital transformation, cloud computing, and artificial intelligence.
Accenture currently has
209 open roles
on FindRole.
Listed pay typically runs
$94,400–$266,300
across 181 roles with salary data.
AI Architect - FDE Associate Director
The AI Architect - FDE Associate Director joins the AWS Practice to design and scale enterprise-grade Agentic AI platforms across public, private, and sovereign cloud environments. This role involves architecting full-stack AI solutions using Generative AI, Foundation Models, and Knowledge & Data Engineering to solve complex business problems at scale. Key responsibilities include developing agent orchestration frameworks, managing LLMOps and MLOps pipelines, ensuring AI governance and security, and designing knowledge architectures like knowledge graphs and semantic layers. The successful candidate will utilize Python, Java, and tools such as LangGraph, CrewAI, AutoGen, and Amazon Bedrock AgentCore. They will also leverage cloud-native services to build reusable components and reference architectures. This role focuses on the technical challenge of moving AI systems from ideation through production deployment while optimizing for performance, cost, reliability, and trust.
Design and scale enterprise-grade Agentic AI platforms across public, private, and sovereign cloud environments.
Develop architectural blueprints for multi-agent systems, including security, governance, and data layers.
Create knowledge architectures using knowledge graphs and semantic layers to enable large-scale AI agents.
Build financial viability models and select technologies for full-stack AI platform implementation.
Establish AgentOps, LLMOps, and MLOps pipelines to manage the lifecycle of machine learning and large language models.
Design reusable AI components and solution patterns to ensure consistent delivery across multiple engagements.
Troubleshoot and optimize AI systems for performance, cost efficiency, reliability, and trust.
Lead technical workshops with clients to define requirements and finalize total cost of ownership for AI solutions.
What we're looking for
Must have a Bachelor's degree or equivalent (minimum 12 years of experience).
Must have an Associate Degree with at least 6 years of work experience.
Minimum of 12 years of experience in Python, Java, or equivalent.
Minimum of 6 years of experience with key AI technologies from public cloud providers, open source, and third-party tooling.
Minimum of 4 years of experience designing, engineering, and operationalizing large-scale AI/ML solutions on at least one major public cloud.
Minimum of 2 years of experience with AI platforms (Claude, open-source), agentic orchestration tools (LangGraph, CrewAI, AutoGen), and MLOps/LLMOps practices.
Must have experience designing and implementing scaled Agentic AI and Generative AI solutions that are in operations.
Must have experience designing and implementing Agentic AI and Generative AI platforms and frameworks used by multiple AI solutions.
Python
Java
Generative AI
LLM
LangGraph
CrewAI
AutoGen
Amazon Bedrock
Azure AI Foundry
Google Vertex AI
Anthropic Claude
MLOps
LLMOps
Knowledge Graphs
Data Engineering
Observability