Job Title:  Senior Consultant | Full Stack | Mumbai | Engineering | Platform Development & Integration

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 enterprise digital transformation engagements by combining business consulting, product strategy, and AI solution architecture. Partner with senior client stakeholders to define product vision, architect AI-powered solutions, and lead delivery teams using modern Agentic AI frameworks and cloud platforms.

Key skills required:

·       Demonstrated hands-on experience in designing, developing, and deploying Agentic AI solutions using single-agent and multi-agent architectures for complex enterprise use cases.

·       Strong expertise in building and orchestrating multi-agent systems including planning, reasoning, task delegation, tool usage, and agent-to-agent communication workflows.

·       Proven experience implementing Retrieval-Augmented Generation (RAG) solutions using vector databases, hybrid search, semantic retrieval, document processing pipelines, and enterprise knowledge repositories.

·       Deep understanding of agent memory architectures including short-term memory, long-term memory, episodic memory, semantic memory, and contextual memory management techniques.

·       Hands-on experience with agent orchestration frameworks such as LangGraph, Google Agent Development Kit (ADK), Microsoft Agent Framework (MAF), Semantic Kernel

·       Experience integrating Large Language Models from OpenAI, Azure OpenAI, Anthropic Claude, Gemini, and open-source models into production-grade agentic applications.

·       Strong knowledge of LLM evaluation frameworks, benchmarking methodologies, agent testing strategies, and automated quality assessment for AI systems.

·       Experience implementing AI guardrails, safety controls, policy enforcement, content moderation, security controls, and responsible AI practices for enterprise deployments.

·       Hands-on experience designing and leveraging Knowledge Graphs, graph databases, and semantic relationship modeling to enhance retrieval and reasoning capabilities.

·       Strong proficiency in Python development, API integrations, tool development, workflow automation, and cloud-native AI application development.

·       Experience with observability, tracing, monitoring, and debugging of AI agents using modern AIOps and telemetry frameworks.

·       Ability to optimize agent performance across accuracy, latency, scalability, cost efficiency, reliability, and governance requirements.

Skills & Competencies

Agentic AI Development and Multi-Agent System Design

LangGraph, Google Agent Development Kit (ADK), Microsoft Agent Framework (MAF), Semantic Kernel, CrewAI, AutoGen

Retrieval-Augmented Generation (RAG) Architecture

Agent Memory Management and Context Engineering

Knowledge Graphs and GraphRAG

LLM Orchestration and Tool Calling Frameworks

AI Evaluation Frameworks (LLM Evals, Agent Evals, Benchmarking)

AI Guardrails, Safety Controls, and Responsible AI, Observability, Monitoring, Logging, and Tracing for AI Agents

AI Governance, Security, Compliance, and Auditability

Prompt Engineering and Agent Reasoning Strategies

Vector Databases (Azure AI Search, Pinecone, Weaviate, Qdrant, ChromaDB)

OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Open-Source LLMs

MCP (Model Context Protocol) and Agent Interoperability

Python, FastAPI, REST APIs, and Backend Engineering

Cloud-Native AI Development on Azure and GCP

Problem Solving, Analytical Thinking, and Enterprise Solution Delivery

Success Metrics

Delivery of scalable GenAI solutions

Performance optimization (latency, cost, accuracy)

Successful deployment of agentic workflows

Improved system reliability

High client satisfaction

Contribution to reusable AI assets

Preferred Qualifications

Education- Bachelor's or Master's Degree in Computer Science, Engineering, Information Systems, or related field.

Certifications in Azure, Google Cloud, AI Engineering, or Enterprise Architecture preferred. Experience designing and delivering enterprise AI, GenAI, or Agentic AI solutions at scale.

Proven consulting experience working with CXOs, business leaders, and technology stakeholders.

Experience across banking, insurance, manufacturing, healthcare, or enterprise transformation programs is highly desirable.

Location and Way of Working:

Base location: Mumbai / Pune

Hybrid / flexible working model