Overview The GenAI Technical Business Analyst will be pivotal in connecting business objectives with advanced generative AI technologies. This role will focus on the technical development, deployment, and optimization of GenAI solutions, ensuring alignment with business strategies and technological advancements. Responsibilities - Drive the ideation, development, and deployment of GenAI solutions, with a focus on leveraging Foundation Models, Large Language Models (LLMs), and LLMOps frameworks. Prioritize scalability, ROI, and strategic business impact. - Work closely with data scientists, AI developers, and engineers to align GenAI models with business needs, ensuring models meet genetic research and other domain-specific requirements. - Develop and manage detailed GenAI product roadmaps, including timelines, usability metrics, and budget adherence. Ensure alignment with organizational goals and compliance standards. - Create comprehensive technical specifications, including process flow diagrams, user journeys, and wireframes for GenAI applications. Ensure documentation is clear and accessible for cross-functional teams. - Conduct thorough technical analysis of AI algorithms during the Proof of Concept (POC) and Discovery phases. Provide technical recommendations to enhance model performance and business integration. - Continuously evaluate and recommend cutting-edge GenAI technologies, tools, and platforms (e.g., RAG, LangChain) to improve system performance, scalability, and robustness. - Organize and lead technical workshops to identify and explore new opportunities where GenAI can optimize business processes, enhance productivity, and drive innovation. - Develop and maintain detailed technical documentation for all GenAI products, including technical requirements, use cases, and compliance considerations related to data privacy and security. - Stay updated on the latest trends in the GenAI ecosystem. Evaluate the technical feasibility and strategic value of emerging GenAI solutions and recommend adoption strategies. - Collaborate with data engineering teams to ensure seamless data preparation, integration, and management for GenAI model training and deployment. Qualifications Bachelor’s or master’s degree in computer science, Data Science, or a related technical field. - Demonstrated ability to translate complex technical concepts into actionable business strategies. Experience in data-driven decision-making processes. - Strong communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders. - Proven track record in managing and delivering AI/ML projects, with a focus on GenAI solutions, in large-scale enterprise environments - Minimum of 12 years in data product management with a strong focus on AI/ML technologies, particularly in the GenAI domain. - Deep understanding of GenAI, Foundation Models, LLMs, LLMOps, Retrieval-Augmented Generation (RAG), and LangChain. Proven ability to apply these technologies in enterprise environments. - Proficient in data analysis, model validation, and visualization tools (e.g., Python, R, Tableau). Experience with AI model lifecycle management, including training, validation, and testing methodologies. - Strong background in software development life cycles, particularly Agile methodologies, with a focus on AI/ML project delivery. - Familiarity with cloud-based AI/ML platforms and services (e.g., AWS, Azure, GCP) and experience in integrating these with GenAI solutions. - In-depth understanding of data privacy, security considerations, and compliance standards relevant to AI applications.
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