Sneha Katakam

Collaborated in a fast-paced environment to support AI engineering by collecting use-case data, analyzing AI performance against user data, and providing actionable feedback to improve AI. Created and executed prompts, documented tool interactions, and explained chain-of-thought reasoning during tool use. Aligned prompts with business logic, user expectations, and language best practices; coordinated with HR, operations, and engineering to address workforce planning needs; conducted multi-level quality checks to ensure consistency in feedback on AI prompts and maintain high standards for documentation when AI fails.

Provided high-quality, fully human-generated annotations for short speech recordings including labelling and creatively describing speech characteristics such as audio quality, voice traits, speaking style, and delivery. Ensured accuracy and consistency in annotations to enhance speech recognition and analysis models. Applied linguistic and acoustic analysis to assess vocal attributes including tone, pitch, articulation, and emotional expression. Managed large datasets with diverse speech samples, maintaining precision under tight deadlines.

Working collaboratively in a fast-paced remote environment, executing different use cases for data collection supporting AI engines. Conduct data analysis comparing AI performance to user data, provide feedback to improve AI, create and execute prompts, learn new software, and provide supporting documentation when AI fails. Describe tool interactions with websites and offer chain-of-thought reasoning during runs. Design, test, and refine prompts to improve AI interactions aligning with business logic and user expectations. Collaborate with HR, operations, and engineering teams to understand workforce planning needs. Conduct multi-level quality checks to ensure consistency and alignment with project standards.