Join Deloitte's Technology & Transformation practice to architect and lead the development of enterprise Agentic AI platforms on AWS. This role involves defining platform strategy, operating models, governance, and engineering standards to drive large-scale AI adoption within enterprises.

Leverage your expertise in Generative AI and cloud technologies to shape the future of AI platforms. You will collaborate with executive stakeholders to ensure robust, scalable, and secure AI solutions are implemented.

This is a hybrid role based in Mumbai or Pune, offering a flexible working model.

Lead the architecture, design, and development of enterprise Agentic AI platforms on AWS. Collaborate with executive stakeholders to define platform strategy, operating models, and governance frameworks. Establish engineering standards and reusable AI capabilities for enterprise-wide adoption. Design and develop Agentic AI solutions using single-agent and multi-agent architectures. Define reference architectures for complex AI systems, including human-in-the-loop components. Establish AI governance, guardrails, and responsible AI practices.

Design and implement cloud-native AI platforms leveraging various AWS services. Build enterprise integration architectures that connect AI platforms with existing business systems. Drive the adoption of platform accelerators and develop roadmaps for enterprise AI transformation. Manage stakeholder relationships, including direct interaction with CXOs and enterprise architecture teams.

Proven experience architecting enterprise-scale AI and Agentic AI platforms on AWS is essential. Hands-on expertise in designing and developing Agentic AI solutions with single-agent and multi-agent architectures is required. Strong understanding of AWS-native AI services like Amazon Bedrock, SageMaker AI, and OpenSearch is critical.

Expertise in defining RAG and GraphRAG architectures, along with knowledge of memory architectures (short-term, long-term, semantic, episodic) is necessary. Experience defining engineering standards using frameworks like LangGraph, CrewAI, or AutoGen is highly valued. Deep knowledge of AI governance, Responsible AI, security controls, and LLMOps/AgentOps is a must.

Ability to establish architecture review boards, engineering governance processes, and adoption roadmaps is expected. Strong stakeholder management skills, including experience working with CXOs, are also key requirements for this role.