Key Skills & Responsibilities

• Experience in LLMs, NLP, AI Chatbots, and AI process automation
• Experience working with AI engineers, data scientists, and stakeholders to develop AI chatbots, virtual assistants, and automation workflows and deliver AI-driven insights
• Strong communication and presentation skills, with the ability to explain technical concepts to non-technical stakeholders.
• Ability to work independently as well as part of a team in a fast-paced environment.
• Be able to communicate and present effectively to stakeholders.
• Gather and document functional and technical requirements for AI-powered automation
• Stay up to date with advancements in AI, machine learning, Agents, and data analytics techniques to continuously improve processes and solutions.
• Establish best practices, standards, and methodologies for data science and AI projects.
• Drive the adoption of cutting-edge technologies and methodologies in the field of AI and machine learning
• Change Management: strong ability to influence and make a case for change, to individual contributors and leaders, and make change stick.

• Value Realization: be able to show sustained value realization and business results

Technical skills:

• Proficiency in AI/GenAI technologies and frameworks.
• Experience with machine learning models and MLOps practices.
• Familiarity with OpenAI and its applications in generative AI.
• Strong programming skills in Python, R, or Java.
• Experience of a modern Tech stack, and the force.com platform with tools such as Eloqua, Gainsight, SFDC, Certinia, and Microsoft automation platform 

Preferred Experience

• 3-5+ years of experience as a Business Analyst/Technical BA in Conversational AI, Generative AI or AI-driven automation projects
• Deep understanding of AI technologies and their business applications
• Knowledge of data privacy regulations and ethical considerations in AI.
• Strong problem-solving skills and ability to communicate insights effectively.
• Experience working with cross-functional teams, including business stakeholders, IT, and data engineers.
• Will have worked in a global organization, spanning time zones and geographies