Advanced AI Architect

Accenture•Kirkland, WA

1d•Hybrid

About The Position

As an Advanced AI Architect, you will be responsible for designing and delivering full stack AI architecture for an AI platform, AI product, or AI engagement on public, private or sovereign clouds. You’ll architect enterprise grade AI platforms and solutions for scalability, security, governance and performance that meet our client’s business needs. In that role you will be using the latest innovations in AI Agents, Generative AI, Foundation Models, Knowledge & Data Engineering. You will be designing and implementing cutting edge proof-of-concepts and pilots to demonstrate the capabilities of AI technologies to solve complex business problems and for enterprise readiness. This is a high-impact role where your contributions will shape the future of AI systems in the enterprise to deliver unprecedented business value.

Requirements

Minimum of 2 years of experience designing and implementing scaled Agentic AI and Generative AI solutions that are in operations.
Minimum of 2 year of experience in designing and implementing Agentic AI and Generative AI platforms and frameworks used by multiple AI solutions
Minimum of 5 years of experience in designing, engineering & operationalizing large scale AI/ML solutions on at least one of the large public cloud platforms using latest cloud native AI services and frameworks, open-source technologies and 3rd party tools.
Minimum 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 (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)

Responsibilities

Lead AI architecture & technical design workshops with client and Accenture teams
Collaborate with client teams to finalize architectural requirements for AI solutions.
Evaluate, rationalize and select technologies required for putting together the full stack of an AI platform or AI system
Estimate design alternatives, effort, timeline, roadmap for deploying AI solutions.
Develop TCO models and assess financial viability of AI platforms and solutions.
Design and document architectural alternatives, technology choices and recommendations
Identify, define, facilitate alignment of key architectural decisions required for AI solutions
Design and document multi-agent architecture blueprints, AI security architecture blueprints, AI runtime architecture blueprints, AI governance solution blueprints, AI DevOps architecture blueprints, AI infrastructure architecture blueprints, multi-agent solution blueprints, knowledge and data layer blueprints.
Design the knowledge architecture consisting of knowledge graphs, semantic layers for enabling AI Agents.
Incorporate AI Security in platforms and solutions.
Design and document solutions for AI security, governance, observability.
Design and document AgentOps and LLMOps solutions.
Recommend design optimizations and improvements for performance, cost, reliability, trust.
Implement AgentOps/LLMOps, AI Governance, AI Security, AI Observability solutions
Design/Build reusable AI components, AI agents and solution patterns for Advanced AI systems and platforms.
Troubleshoot, Analyze and optimize performance of AI systems, AI agents and platforms