Join a leading Technology & Transformation practice to spearhead enterprise digital transformation initiatives. This role involves a blend of business consulting, product strategy, and AI solution architecture. You will collaborate with senior client stakeholders to shape product visions, design advanced AI-powered solutions, and guide delivery teams utilizing cutting-edge Agentic AI frameworks and cloud platforms.

Lead complex digital transformation projects by architecting and delivering AI solutions. Engage with C-suite executives and business leaders to define product roadmaps and strategies. Architect and implement robust Agentic AI solutions, including single-agent and multi-agent systems, for enterprise-level challenges. Oversee the development and deployment of Retrieval-Augmented Generation (RAG) pipelines, leveraging vector databases and knowledge graphs. Ensure the integration of Large Language Models (LLMs) from various providers into production-ready applications. Implement AI guardrails, responsible AI practices, and comprehensive monitoring systems. Optimize agent performance for accuracy, latency, cost, and reliability.

Demonstrated expertise in designing, developing, and deploying Agentic AI solutions with single and multi-agent architectures. Strong experience in building and orchestrating multi-agent systems, including planning, reasoning, and task delegation. Proven ability to implement RAG solutions using vector databases and enterprise knowledge repositories. Deep understanding of agent memory architectures and contextual management. Hands-on experience with agent orchestration frameworks like LangGraph, ADK, MAF, or Semantic Kernel. Proficiency in integrating LLMs (OpenAI, Azure OpenAI, Claude, Gemini, open-source) into production applications. Solid knowledge of LLM evaluation, benchmarking, and AI testing strategies. Experience implementing AI guardrails, safety controls, and responsible AI practices. Hands-on experience with Knowledge Graphs and graph databases. Strong Python development skills, API integration, and cloud-native AI development. Experience with observability, monitoring, and debugging of AI agents. Ability to optimize agent performance across various metrics. A Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field is preferred.