Job Description

Position Summary: As an experienced Consultant at Deloitte Consulting Services, you will be responsible for individually delivering high-quality work products within due timelines. You may also mentor and/or direct junior team members and liaise with onsite/offshore teams to understand functional requirements. Our Enterprise Performance team helps organizations transform core business operations through technology, data, and innovation across finance, supply chain, and IT. Within this practice, professionals work with Deloitte client service teams to design and deliver solutions that improve operational performance, enable digital transformation, and drive measurable business outcomes.

Work You'll Do:
- Advise clients on AI platform selection for sourcing, procurement, and supplier management environments by evaluating platform fit, integration complexity, data residency, licensing, and business readiness.
- Design and prototype agentic artificial intelligence workflows for use cases such as supplier qualification, request for quotation and request for proposal automation, contract review, purchase order exception handling, invoice matching, and spend anomaly detection.
- Apply large language model orchestration, retrieval-augmented generation, tool use, memory management, and human-in-the-loop patterns to develop practical proof-of-concept solutions.
- Assess procurement data readiness, including supplier master data, spend classifications, contract metadata, and integration patterns across enterprise resource planning and Source-to-Pay platforms.
- Support client delivery through workstream management, business case development, technology roadmaps, prototype demonstrations, and client-ready recommendations.

Location: Bengaluru / Hyderabad / Pune / Chennai
Shift Timings: 11 AM to 8 PM or 2 PM to 11 PM IST as per business requirements

Required Qualifications

Technology consulting experience
Enterprise AI implementation
Data strategy
Enterprise transformation
Hands-on experience with major AI platforms (Azure AI, Copilot Studio, Vertex AI, Gemini, AWS Bedrock, Salesforce Agentforce, ServiceNow AI, IBM watsonx)
Building and deploying AI agents and AI-powered workflows
Multi-agent orchestration
Tool use
Retrieval-augmented generation (RAG)
Human-in-the-loop patterns
LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen)
AI platform evaluation across integration complexity, data residency, licensing, and cost
Procurement or supply chain data analysis
Data quality assessment
Data architecture
Spend intelligence solutions

Preferred Qualifications

Source-to-Pay processes expertise
SAP Ariba
Coupa
Ivalua
GEP SMART
Zip
ORO Labs
Tonkean
Prompt engineering
Grounding techniques
Context window management
Function calling
Fine-tuning approaches
AI governance and regulatory frameworks (EU AI Act, NIST AI Risk Management Framework, ISO/IEC 42001)
Cloud data platforms (Snowflake, Azure Synapse, BigQuery)
Enterprise integration patterns
API connectivity
ERP connectivity
UNSPSC
AI-assisted spend classification

Skills Required

Generative AIArtificial IntelligenceLarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Multi-Agent OrchestrationLangChainLangGraphLlamaIndexSemantic KernelAutoGenMicrosoft Azure AIGoogle Vertex AIAWS BedrockSAP AribaCoupaPrompt EngineeringSupply Chain Data AnalysisEnterprise Integration Patterns