AI Business Analyst

Protiviti India; India; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

Protiviti India is seeking an accomplished AI Business Analyst or Consultant specializing in Generative AI and autonomous agentic solutions for complex enterprises. You will translate advanced AI architectures into actionable business capabilities and serve as a bridge between technical teams and executive leadership.

Responsibilities include defining functional architectures, states, and governance across the transformation lifecycle, with emphasis on explainability, transparency, and

Qualifications

• Autonomous AI expertise and multi-agent orchestration design experience.
• Memory management, short/long-term memory architectures and persistent knowledge retention.
• RAG, vector databases, embeddings and knowledge graph integrations.
• Multi-modal interfaces and browser automation familiarity.
• Ability to communicate AI governance, explainability and ethics to leadership.
• Strong consulting skills and Agile delivery lifecycle experience.

Responsibilities

• Evaluate and define functional architectures for Generative AI across business units.
• Bridge technical teams and executives by translating LLM capabilities into business requirements.
• Define specifications for stateful agents and contextualization layers.
• Design traceability, explainability, safety and governance frameworks for AI initiatives.
• Articulate interface requirements for multi-modal interactions and workspace integrations.
• Support transformation delivery and align milestones with enterprise goals.

Skills

Autonomous AI & Agentic Frameworks

Stateful Agents

RAG & Knowledge Layer Structuring

Continuous Learning & Interfaces

Explainability & Governance

Technical Consulting & Lifecycle

Tools

LangChain

Azure OpenAI

Knowledge Graphs

Job description

1. Role Overview

We are seeking an accomplished AI Business Analyst or Consultant with deep expertise in Generative AI and autonomous agentic solutions for complex enterprise settings. The successful candidate will evaluate, guide, and translate sophisticated AI architecturesincluding multi-agent orchestration, stateful memory management, and advanced RAG pipelinesinto clear, impactful business capabilities. Operating as a pivotal advisory bridge between technical engineering and organizational leadership, this role champions AI explainability, transparency, and governance across the transformation lifecycle. The ideal professional combines solid analytical rigor, mastery of modern LLM frameworks, and exceptional consultative communication to shape scalable enterprise AI strategies.

2. Key Responsibilities

• Evaluate, guide, and define functional architectures for Generative AI and autonomous agentic solutions across multi-functional business units.
• Bridge technical engineering teams and executive stakeholders by translating complex LLM capabilities, agent memory models, and RAG architectures into clear business requirements.
• Define specifications for stateful agents, knowledge retention mechanisms, and contextualization layers using vector databases and knowledge graphs.
• Ensure AI transparency, auditability, and ethical governance by designing comprehensive traceability and explainability frameworks across all AI initiatives.
• Assess and articulate interface requirements for multi-modal agent interactions, browser automations, and seamless workspace integrations.
• Support business analysis and delivery governance across the complete transformation lifecycle, aligning AI implementation milestones with overarching enterprise goals

3. Mandatory Skills

• Autonomous AI & Agentic Frameworks: Deep conceptual and architectural understanding of multi-agent orchestration and frameworks (e.g., LangChain, AutoGen, LangGraph, CrewAI, Azure OpenAI).
• Stateful Agents & Memory Management: Robust knowledge of designing AI agents with short/long-term memory capacities, dynamic data handling, and persistent knowledge retention.
• RAG & Knowledge Layer Structuring: Comprehensive expertise in Retrieval-Augmented Generation (RAG) paradigms, vector databases, embeddings, and knowledge graph integrations for enterprise contextualization.
• Continuous Learning & Interface Concepts: Strong grasp of reinforcement and self-learning mechanics, multi-modal input processing (voice, video), and browser automation environments.
• Explainability & Governance: Demonstrated ability to evaluate, communicate, and enforce AI traceability, explainability, safety, and governance across enterprise solutions.
• Technical Consulting & Lifecycle Delivery: Exceptional communication and consultative skills with proven experience in Agile transformation delivery lifecycles.

4. Preferred Skills

• Domain background or transformation project experience within corporate, commercial, or retail banking and financial institutions.
• Familiarity with sandbox design, secure development environments, and workspace tools for testing agentic automation workflows.
• Prior hands-on software development or implementation exposure with Python, LLM APIs, and AI agent frameworks (desirable but not mandatory).

5. Experience Required

Minimum 7 years of overall professional experience in technical consulting, business analysis, or technology project delivery within enterprise environments.

At least 3 years of dedicated focus in Artificial Intelligence, Machine Learning, Generative AI, RAG architectures, or agentic AI platforms.