2-3 yrs of experience in analyzing recurring issues, corrections, and data to identify root causes and improvement opportunities.
Convert business rules and operational knowledge into AI requirements, validation checks, prompts, and test cases.
Work with Product, Engineering, AI/ML, and Implementation teams to improve AI extraction, mapping, classification, and automation workflows.
Evaluate and validate LLM/AI outputs, identify failure patterns, and improve accuracy.
Build reusable AI workflows, prompts, rules, and evaluation datasets.
Measure improvements in accuracy, manual effort, and operational efficiency.
Maintain clear documentation and knowledge bases for reusable solutions.
Candidates whose primary experience is in Power BI, SQL, MIS, or traditional Data/Reporting Analytics should not apply.
OneOrigin, where innovation meets imagination! Based in Scottsdale, AZ and Bangalore, India, we’re on a mission to harness the power of AI to transform the way Higher Education
institutions operate. Our cutting-edge software solutions streamline administrative processes, enhance student engagement, and empower data-driven decision-making.
Whether it’s automating tasks, providing actionable insights, or improving learning outcomes, we make AI accessible and impactful for colleges and universities. #LI-Onsite
Summary
Convert business rules into AI requirements, prompts, validation checks, and test cases to improve extraction, mapping, and classification workflows. Evaluate LLM outputs, identify failure patterns, and build reusable prompts and evaluation datasets. Requires 2-3 years analyzing recurring issues and data for root causes.
Responsibilities
Convert business rules into AI requirements, validation checks, prompts, and test cases; improve AI extraction, mapping, classification, and automation workflows; evaluate and validate LLM/AI outputs; build reusable AI workflows and evaluation datasets; measure accuracy and efficiency improvements
Experience requirements
2-3 yrs of experience in analyzing recurring issues, corrections, and data to identify root causes and improvement opportunities