AI Business Analyst

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.