Join our dynamic Consulting team as an Agentic AI Architect and spearhead the creation of advanced AI agent ecosystems. This role involves designing sophisticated solutions using cutting-edge technologies like LLMs, multi-agent frameworks, RAG, and orchestration platforms.

You will be instrumental in defining the overall solution architecture and charting technical strategies. Collaboration with diverse, cross-functional teams will be key to delivering AI solutions that are not only scalable and secure but also production-ready.

Lead the design and development of enterprise-grade Agentic AI solutions and complex multi-agent ecosystems. Define comprehensive end-to-end architecture, encompassing AI governance, scalability, security, and integration strategies. Implement AI solutions leveraging LLMs, RAG, and advanced multi-agent orchestration frameworks. Drive critical technical solutioning and architecture decisions, ensuring seamless integration with existing enterprise systems. Collaborate effectively with cross-functional teams and stakeholders to guarantee successful solution delivery. Identify potential technical risks and architect robust, scalable solutions to mitigate them. Provide essential technical leadership and guidance to engineering teams.

A minimum of 10 years in overall software engineering, with at least 4 years dedicated to Generative AI. Proficiency in Python and frameworks such as LangGraph, LangChain, AutoGen, CrewAI, and MCP. Extensive experience in Agentic AI, multi-agent architectures, LLMs, RAG, and AI orchestration is essential. Demonstrated hands-on experience with vector databases and major cloud platforms (AWS, Azure, GCP). Solid understanding of AI system design, API integration, MLOps, and prompt engineering principles. Experience in enterprise architecture, AI governance, security, and scalability. Exceptional technical leadership, stakeholder management, and problem-solving capabilities.