Pranav S. - AI Operations & Backend Engineering Intern

College Park, United States

Experience

Jun 2025 - Aug 2025

3 months

Kansas City, United States

Built an AI powered end to end PaaS platform for T-Mobile to streamline the testing lifecycle that leverages Predictive Testcase Selection, saving close to $25 per hour for our client by enabling the left shift of testing in projects, reducing delivery time by 80%.
Tailored a RAG based LLM approach for resolving test issues, with dependency mapping, node knowledge graph and connectors for various input types. Engineered an intermediatory CLI that prevented MIM, DoS and other business logic abuse.
Implemented an accuracy check for each suggestion in the LLM mitigator, achieving an average accuracy greater than 96.7%.

Apr 2023 - Nov 2023

8 months

Bengaluru, India

Developed the first-ever AI-driven forensic watermarking system using compartmentalized hue analytics, achieving 73.33% traceback accuracy and reducing forensic analysis time by 90%.
Engineered a median hue-based tracking algorithm with OpenCV, TensorFlow, and SSIM, enabling piracy source identification across varying camcorder conditions.
Published findings in IEEE ICDDS 2023, introducing an industry-first computer vision-based piracy detection method for tracing unauthorized film recordings to specific theatres.

Aug 2022 - Sep 2022

2 months

Bengaluru, India

Implemented Data Exchange Factory (DxF), a real-time EDI (HL7) to FHIR conversion pipeline, enabling seamless healthcare and insurance data interoperability. Built data catalogs, automated transformations, and enabled real-time FHIR streaming via Kafka.
Optimized a geospatial TSP solver using Java and JavaScript, enhancing route planning efficiency across India by incorporating real-world travel constraints and cutting cost by 80%. Designed a rule-based book recommender for a mobile librarian, saving engagement time by 50%.
Refactored and enhanced software architectures while solving complex C#, Kotlin, Java, Dart, and JavaScript challenges. Led case studies on FHIR adoption in medical data management and maintained codebases via Azure integration.