Job Description

At Verint, we believe customer engagement is the core of every global brand. Our mission is to help organizations elevate Customer Experience (CX) and increase workforce productivity by delivering CX Automation. We hire innovators with passion, creativity, and drive to answer constantly shifting market challenges and deliver impactful results for our customers. Our commitment to attracting and retaining a talented, diverse, and engaged team creates a collaborative environment that openly celebrates all cultures and affords personal and professional growth opportunities. Learn more at www.verint.com .



Role Summary


In this role, you will leverage advanced technical and linguistic skills to become an expert in our AI Orchestration platform: IVA Studio. You will build upon a deep expertise in Conversational AI and Generative AI to help users and teams understand how to best use IVA Studio tools in their business, empowering them to succeed independently and collaboratively. Your work will span departments, enabling you to translate complex technical concepts into practical solutions that support customer and internal needs alike.


Key Responsibilities


Lead training and enablement for IVA Studio, ensuring users understand and adopt the tool effectively for their immediate business needs and future goals. Collaborate with Sales and Product teams to align learning initiatives with departmental goals and customer needs. Build strategic partnerships with internal teams to co-create innovative learning solutions. Troubleshoot challenges with customers, partners and internal teams and provide guidance to optimize their IVA solutions and encourage self-sufficiency. Document processes, learning materials, and strategies with clarity and precision for all different levels. Experiment with latest product releases and emerging technologies to continuously improve personal expertise and future learning experiences. Develop and deploy solutions leveraging Large Language Models (LLMs) such as GPT, Claude, or open-source alternatives for enterprise use cases.*
Design and implement Retrieval-Augmented Generation (RAG) pipelines to enhance LLM performance with domain-specific knowledge.*
Apply Model Customization & Prompting (MCP) techniques including fine-tuning, prompt engineering, and instruction tuning to optimize model outputs.*
Build and orchestrate Agentic AI systems, enabling autonomous agents to plan, reason, and act in complex environments.*
Design and manage Agent-to-Agent (A2A) communication protocols for collaborative multi-agent systems.*
Collaborate with cross-functional teams to integrate AI capabilities into products and services, ensuring scalability and reliability.*
Stay current with advancements in generative AI, agent frameworks (e.g., LangChain, AutoGen, CrewAI), and foundation model APIs.*
Evaluate and benchmark LLM performance using metrics such as factuality, coherence, latency, and cost-efficiency.*
Ensure ethical and responsible AI practices, including bias mitigation, explainability, and data privacy.*