Business Analyst - Gen AI

We are seeking a strong AI Engineer or consultant profile with extensive knowledge of generative AI solutions used in complex business settings. The ideal candidate will have a deep, comprehensive understanding of AI frameworks and techniques, particularly in autonomous agent development, memory management, contextualization with LLMs, and self-learning systems. In this role, the ability to explain, evaluate, and guide technical solutions is critical, even if hands-on coding or implementation is not the primary focus.

Responsibilities:

• Autonomous AI Agent Development: Strong conceptual grasp of leveraging LLMs and agentic AI frameworks to develop collaborative AI agents and orchestrate agent interactions.
• Stateful Agents: Clear understanding of designing agents with long- and short-term memory capacities, data handling, and knowledge retention.
• Agent Contextualization: Comprehensive knowledge of methods for adapting LLMs or using RAG (Retrieval-Augmented Generation) to incorporate organization-specific context and manage nuanced requirements.
• Self-Learning and Reinforcement: Ability to articulate how AI agents can be designed for self-improvement and continuous learning.
• Comprehensive Interface Development: Awareness of end-to-end interface requirements, including support for multimodal inputs (voice, video), browser automations, and seamless user interaction.
• Traceability and Explainability: Capability to ensure, demonstrate, and communicate transparency and explainability within the AI process.

Requirements:

• Degree in computer science, AI, machine learning, data science, or similar.
• Minimum 5 years, with at least 3 years focused on AI/machine learning, GenAI, RAG, or agentic platforms. Deep technical understanding is essential; hands-on implementation is desirable but not mandatory.
• In-depth knowledge of LLM/agent frameworks like Azure OpenAI, LangChain, AutoGen, LangGraph, and CrewAI.
• Understanding of how RAG-based GenAI solutions are developed and how knowledge layers for AI agents are structured (e. g., vector DB, knowledge graphs, etc. ).
• Familiarity with design and operation of sandbox environments, browser automations, and workspace tools for agentic solutions.
• Prior experience as a business analyst in AI/tech projects and familiarity with project delivery life cycles such as agile.
• Banking experience is beneficial.
• Exceptional communication skills, with the ability to clearly explain technical details and rationale.