Mahnoor Ejaz

Designed and deployed conversational AI agents using prompt engineering and tool-based architectures with RAG-assisted retrieval, automating 60-80% of tenant and prospect interactions. Built a proactive messaging system within the LeasingBot using Camunda, reducing manual outreach by ~70% and saving ~$450K annually.

Developed an AI bot using AutoGen, GPT, and RAG to autonomously generate unit tests across codebases, reducing manual testing effort. Built a GPT-based summarization system for claims data, cutting manual processing effort by 80%.

Transformed experimental models into a robust ML pipeline using PySpark, managing strategic migration and leading end-to-end automation. Spearheaded optimization of a customized ML pipeline, reducing runtime from 24 hours to 3 hours and cutting resource consumption by 96%.

Upgraded and maintained a Java Spring Boot API codebase on Microsoft Azure, ensuring optimal performance and security compliance. Successfully migrated multiple Java Spring Boot applications from Azure to a private cloud, integrating CI/CD for efficient updates.

Gained hands-on experience in technology operations and support within a leading telecommunications company.

Grade: 3.74/4.0

Pursued a Master of Philosophy in Computer Science with a cumulative GPA of 3.74/4.0.

Grade: 3.63/4.0

Completed a Bachelor of Science (Hons.) in Computer Science with a cumulative GPA of 3.63/4.0.