Demonstrates intimate-level abilities with, and/or a proven record of success directing efforts in the majority of the following areas:

• Managing development teams in building of GenAI solutions, including but not limited to prompt engineering, general all-purpose programming (e.g., Python), testing, communication of results, front end and back end integration, and iterative development with clients;

• Leading a team to document and analyze business processes for Generative AI opportunities, including gathering of requirements, creation of initial GenAI hypotheses, and development of GenAI solution approach;

• Collaborating with client team to understand their business problem and select the appropriate models and approachesÊfor GenAI use cases;

• Managing teams to process unstructured and structured data to be consumed as context for LLMs, including but not limited to embedding of large text corpus, generative development of SQL queries, building connectors to structured databases;

• Directing architects to design and solution GenAI architectures for clients, specifically for plugin based solutions (i.e., ChatClient application with plugins) and custom GenAI application builds;

• Directing data engineers and other data scientists to deliver efficient solutions to meet client requirements;

• Managing daily operations of a global data and analytics team on client engagements, review developed models, provide feedback and assist in analysis;

• Facilitating and conducting executive level presentations to showcase GenAI solutions, development progress, and next steps;

• Managing associates and senior associates through coaching, providing feedback, and guiding work performance;

• Leading business development activities for clients, including but not limited to facilitating the sales cycle of GenAI proposals; and,

• Leading internal asset development to build foundational GenAI practice.

Demonstrates intimate level abilities and/or a proven record of success learning and performing in functional and technical capacities, including the following areas:

• Managing GenAI application development teams including back-end and front-end integrations;

• Using Python (e.g., Pandas, NLTK, etc.), common LLM development frameworks (e.g., Langchain, Semantic Kernel), Relational storage (SQL), Non-relational storage (NoSQL);

• Vectorization and embedding, prompt engineering, RAG (retrieval, augmented, generation) workflow dev;

• Possessing hands on experience with Azure, AWS, and / or Google Cloud platforms;

• Demonstrating experience with Git Version Control, Unit/Integration/End-to-End Testing, CI/CD, release management, etc.; and,

• Delivering successful technology creation, functional code, AI solutions and Data Platforms.