Job Title:  Manager | Full Stack Architect | 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-scale Agentic AI platform strategy, architecture, and transformation engagements. Partner with executive stakeholders to define AI platform vision, reference architectures, governance models, operating frameworks, and engineering standards for building and scaling Agentic AI capabilities across the enterprise.

Key skills required:

·       Proven experience architecting enterprise-wide Agentic AI platforms supporting hundreds of use cases, agents, and development teams.

·       Deep expertise defining reference architectures for single-agent, multi-agent, and human-in-the-loop AI systems.

·       Strong understanding of Agentic AI platform components including orchestration, memory, knowledge, tooling, governance, observability, and security layers.

·       Experience designing enterprise RAG and GraphRAG architectures leveraging vector databases, knowledge graphs, metadata management, and semantic search.

·       Expertise defining memory management strategies spanning short-term, long-term, episodic, semantic, and organizational memory patterns.

·       Hands-on experience establishing architecture standards across LangGraph, Google ADK, Microsoft Agent Framework, Semantic Kernel, AutoGen, CrewAI, and open-source ecosystems.

·       Experience evaluating and selecting LLMs, foundation models, embedding models, and agent frameworks for enterprise adoption.

·       Deep expertise in AI governance, guardrails, risk management, responsible AI, security controls, compliance, and auditability frameworks.

·       Strong knowledge of LLMOps, AgentOps, evaluation frameworks, observability, tracing, telemetry, and operational excellence practices.

·       Experience designing scalable cloud-native AI platforms on Azure, AWS, and GCP using resilient and modular architectural patterns.

·       Strong enterprise integration experience across APIs, business applications, data platforms, workflow engines, and event-driven ecosystems.

·       Ability to establish architecture review boards, engineering standards, reusable accelerators, and platform adoption roadmaps.

Key Skills & Competencies

·       Agentic AI Platform Architecture and Strategy

·       Enterprise Multi-Agent Reference Architectures

·       Agentic AI Platform Engineering and Operating Models

·       RAG, GraphRAG, Knowledge Graphs, and Enterprise Knowledge Architecture

·       Memory Architecture and Context Management Frameworks

·       LangGraph, Google ADK, Microsoft Agent Framework, Semantic Kernel, AutoGen

·       LLMOps, AgentOps, and AI Platform Operations

·       AI Governance, Responsible AI, Security, Risk, and Compliance

·       AI Guardrails and Trustworthy AI Frameworks

·       Enterprise Architecture and Technology Modernization

·       Cloud Architecture (Azure, AWS, GCP)

·       Observability, Monitoring, Tracing, and Telemetry

·       Model Evaluation, Benchmarking, and Quality Engineering

·       Platform Scalability, Reliability, and Cost Optimization

·       Executive Stakeholder Management and Technology Advisory

·       Enterprise Delivery Leadership and Solution Governance

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