Job Title:  T&T | EAD | AI&Data | Senior Consultant | AI / ML | Bengaluru

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

• Prior role must be as a Data Scientist or ML Engineer for non-GenAI experience
• Production-grade experience building agentic solutions (not just POC/academic)

Key skills required: 

Experience:

• 6-9 years

Key Responsibilities

• Architect and maintain agentic pipelines using LangGraph, CrewAI, and AutoGen
• Implement RAG, prompt engineering, and context/memory/state management
• Develop, fine-tune, and evaluate LLMs (Bedrock, OpenAI, Anthropic)
• Prototype classical ML models (forecasting, clustering, scoring) for hybrid AI systems
• Deploy via SageMaker / ECS / Lambda with observability and monitoring hooks
• Implement guardrails, evaluation metrics, and cost/performance optimization
• Advise BA teams on model selection, explainability, and feasibility
• Python backend development with solid understanding of design patterns

Core Technical Skills

• Agentic Frameworks: LangGraph, CrewAI, AutoGen, LangChain, LlamaIndex
• LLM Development: Fine-tuning (LoRA, PEFT, prompt tuning), embeddings, RAG, prompt engineering
• Context Management: Token sizing, chunking strategies, state & session management in multi-agent systems
• Protocols: MCP (Model Context Protocol), A2A protocol
• Backend Development: Python (async), FastAPI, design patterns
• ML & Evaluation: Statistical ML, feature engineering, MLflow, PyTorch, Scikit-learn, guardrails & evaluation metrics
• Vector Databases: FAISS, Pinecone, Chroma
• Cloud & Deployment: AWS Bedrock, SageMaker, Step Functions, ECR, ECS, Lambda
• Explainability (XAI): SHAP, LIME

Education

• Bachelor's in CS, IT, or ECE – mandatory
• Master’s in data science or relevant field – preferred

Location and Way of Working: 

• Base location: Hybrid (Pan India Deloitte location)