Senior Consultant | Generative AI | Mumbai | Engineering | Platform Development & Integration
•Job requisition ID : 115943
•Location : Mumbai
•Entity : Deloitte Touche Tohmatsu India LLP
The team
Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.
Your work profile
Lead the architecture, design, and development of enterprise Agentic AI platforms on AWS. Collaborate with executive stakeholders to define platform strategy, operating models, governance frameworks, engineering standards, and reusable AI capabilities that support large-scale enterprise adoption.
Key skills required:
•Proven experience architecting enterprise-scale AI and Agentic AI platforms on AWS.
•Hands-on experience designing and developing Agentic AI solutions using single-agent and multi-agent architectures.
•Strong expertise in defining reference architectures for single-agent, multi-agent, and human-in-the-loop systems.
•Deep understanding of AWS-native AI services including Amazon Bedrock, Bedrock Agents, Bedrock Knowledge Bases, SageMaker AI, and OpenSearch.
•Experience designing AI platform capabilities including orchestration, memory, knowledge management, agent runtime services, observability, governance, and security.
•Expertise defining enterprise RAG and GraphRAG architectures leveraging OpenSearch, Neptune, vector stores, metadata management, and semantic retrieval techniques.
•Strong understanding of memory architectures including short-term, long-term, semantic, episodic, and organizational memory patterns.
•Experience defining engineering standards using LangGraph, CrewAI, AutoGen, Semantic Kernel, AWS Strands Agents, and Bedrock Agents.
•Expertise evaluating foundation models, embeddings, agent frameworks, vector databases, and AI technology stacks.
•Strong experience establishing AI governance, AI guardrails, security controls, model risk management, Responsible AI practices, and enterprise compliance frameworks.
•Experience designing LLMOps, AgentOps, platform operations, evaluation pipelines, monitoring, tracing, and observability frameworks.
•Expertise in architecting cloud-native AI platforms leveraging Lambda, ECS, EKS, API Gateway, Step Functions, EventBridge, DynamoDB, Neptune, OpenSearch, and S3.
•Experience building enterprise integration architectures involving APIs, event-driven systems, ERP, CRM, workflow, and data platforms.
•Ability to establish architecture review boards, engineering governance processes, reusable platform accelerators, and adoption roadmaps.
•Strong stakeholder management skills with experience working directly with CXOs and enterprise architecture teams.
Key Skills & Competencies
Agentic AI Platform Architecture
•Enterprise AI Platform Strategy
•Multi-Agent Platform Design
•Agent Runtime and Orchestration Architecture
•AI Platform Engineering Operating Models
AWS AI & Platform Services
•Amazon Bedrock
•Bedrock Agents
•Bedrock Knowledge Bases
•Amazon SageMaker AI
•Amazon OpenSearch Service
•Amazon Neptune
•AWS Lambda
•Amazon ECS / EKS
•Step Functions
•EventBridge
Knowledge & Memory Architecture
•RAG and GraphRAG
•Knowledge Graph Architecture
•Enterprise Knowledge Management
•Agent Memory Frameworks
•Context Engineering and State Management
Operations & Governance
•LLMOps and AgentOps
•Observability, Monitoring, and Telemetry
•AI Governance and Responsible AI
•Security, Risk Management, and Compliance
•AI Guardrails and Trust Architecture
•Platform Reliability and Cost Optimization
Enterprise Architecture
•Cloud-Native Platform Design
•Integration Architecture
•Enterprise Architecture Governance
•Technology Modernization
•Executive Technology Advisory
Success Metrics
•Enterprise adoption of Agentic AI platform capabilities
•Platform scalability, resilience, and security
•Effective governance and risk management
•Reduced solution onboarding timelines
•Increased developer productivity and platform reuse
•Successful delivery of enterprise AI transformation programs
