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Consultant | Full Stack | Mumbai | Engineering | Platform Development & Integration
Deloitte US | Together Makes Progress
Mumbai, IND
Mid
Hybrid
Discovered 1 weeks ago
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- 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 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
Preferred Qualifications
- · 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 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
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