Senior Consultant & Manager | Generative AI | Deloitte

Deloitte Shared Services India; Mumbai, Pune District; Hybrid; INR 1,800,000 - 3,200,000; Full time

Job summary

Deloitte Shared Services India is hiring for Senior Consultants and Managers to architect enterprise-scale Agentic AI platforms on AWS. You will define reference architectures for single-agent and multi-agent systems, integrate Bedrock services, and drive governance, security, and compliance across large enterprises.

Base location is Mumbai with a hybrid/flexible working model. You will collaborate with CXOs and enterprise arch teams to accelerate AI transformation programs and ensure platform

Qualifications

• Proven experience architecting enterprise-scale AI and Agentic AI platforms on AWS.
• Hands-on experience designing Agentic AI solutions using single-agent and multi-agent architectures.
• Strong expertise in reference architectures for single-agent, multi-agent, and human-in-the-loop systems.
• Deep understanding of AWS-native AI services including Bedrock, SageMaker AI, and OpenSearch.
• Experience designing AI platform capabilities: orchestration, memory, knowledge management, observability, governance, and security.

Responsibilities

• Agentic AI platform strategy and governance.
• Multi-Agent platform design and runtime orchestration.
• Platform engineering operating models and memory frameworks.
• Context engineering and state management across environments.
• Enterprise architecture governance and platform accelerators.

Skills

AI platform architecture

Agentic AI

Cloud-Native platform

Governance & compliance

Stakeholder management

Education

Bachelor's or Master's in CS/Engineering/IS

Tools

Amazon Bedrock

Bedrock Agents

Bedrock Knowledge Bases

SageMaker AI

OpenSearch

Neptune

AWS Lambda

ECS / EKS

Step Functions

EventBridge

DynamoDB

S3

Job description

We are hiring Senior Consultants and Managers:

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.

Agentic AI Platform Architecture

• Enterprise AI Platform Strategy
• Multi-Agent Platform Design
• Agent Runtime and Orchestration Architecture
• AI Platform Engineering Operating Models
• Agent Memory Frameworks
• Context Engineering and State Management

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

Preferred Qualifications

• Education- Bachelor's or Master's Degree in Computer Science, Engineering, Information Systems, or related field.
• AWS Solutions Architect Professional, AWS Machine Learning Engineer, AWS AI Practitioner, or equivalent certifications preferred.
• Proven experience designing enterprise AI platforms and cloud modernization initiatives.
• Experience working with Banking, Insurance, Healthcare, Manufacturing, Retail, or Large Enterprise customers.
• Strong consulting, advisory, and stakeholder management experience.

Location and Way of Working

• Base location: Mumbai / Pune
• Hybrid / flexible working model