Agentic AI Architect

The Agentic AI Architect is a role within AI & Data business unit in the Americas for our client, focused on designing next-generation AI solutions that leverage autonomous “agentic” AI systems. This client-facing consulting position involves shaping AI architecture across various industries, delivering vertical-specific solutions for domains like Banking, Financial Services and Insurance. The role involves ensuring AI solutions are innovative, scalable, and responsibly engineered. About the Ro le The Agentic AI Architect is responsible for leading the design and implementation of AI solutions that utilize autonomous agents, ensuring alignment with business goals and industry-specific requirement s. Responsibilit ies Lead AI Architecture Design: Define end-to-end architecture for AI systems incorporating autonomous agents and LLM-based components, ensuring alignment with business goals. Client Workshops & Strategy: Conduct workshops to understand business requirements and identify opportunities for agentic AI, translating business problems into AI architecture blueprints. Multi-Agent Framework Orchestration: Design frameworks for multi-agent systems, defining roles and ensuring robust communication and fail-safes. Integration & Scalability: Outline integration with existing enterprise ecosystems, ensuring scalability and resilience. Leverage Prompt Engineering & RAG: Incorporate advanced prompt engineering techniques and retrieval-augmented generation (RAG) into solution design. Technical Leadership in Delivery: Guide engineering teams through prototyping and solution delivery, troubleshooting high-level architectural issues. Industry-Tailored Solutions: Customize architectural decisions to industry-specific requirements, balancing reusability with necessary adaptations. Emerging Tech Evaluation: Continuously evaluate new tools and methodologies, integrating them into architecture standards. Client Engagement & Travel: Work closely with client technology leaders, presenting architectural proposals and reviewing technical designs, with travel as required. Ethical & Safe Design: Ensure ethical AI and safety considerations are embedded from the architecture stage, documenting and mitigating potential ri sks. Required Skills AI/ML Solution Architecture: Extensive experience in designing and architecting AI or machine learning solutions in an enterprise context. Deep Technical Knowledge: Strong understanding of machine learning and AI techniques, especially Generative AI and large languagemodels. Multi-Agent System Design: Knowledge of multi-agent system patterns and frameworks. Prompt Engineering & RAG: Ability to craft effective prompts and chaining strategies for LLMs, familiar with retrieval-augmented generation methods. AI Ethics & Responsible AI: Strong grasp of AI ethics and safety principles, able to identify ethical risks and design mitigations. Cloud & Distributed Systems: Deep understanding of cloud architecture and distributed systemdesign. Data Management: Solid understanding of data architecture as it relates to AI, including data pipelines, databases, and datalakes. Leadership & Communication: Excellent communication and stakeholder management skills, capable of leading discussions with C-level executives and technical brainstorming with engineers. Consulting and Domain Acumen: Prior consulting or client-facing experience, adept at requirement gathering and crafting proposals. Problem-Solving & Innovation: Creative mindset to devise innovative solutions leveraging AI agents, strong problem-solving skills. Continuous Learning: Demonstrated habit of continuous learning, staying updated via research papers, conferences, or hands-on experimentation. Banking, Financial Services and Insurance domain knowledge will be a plus. Show more Show less