Worked directly with leading AI companies including Anthropic, Mistral, and Cohere to onboard next-generation foundation models and multimodal AI systems at scale

Architected and deployed automated systems for Large Language Model (LLM) performance optimization and benchmarking, reducing manual testing effort from hours to single command execution

Engineered production-scale microservices with sub-millisecond latency and 99.9% availability serving millions of enterprise customers in AWS Bedrock's generative AI platform

Conducted comprehensive security assessments and threat modeling for new AI model integrations, ensuring enterprise-grade security compliance throughout the MLOps lifecycle across Bedrock's model hosting platform

Helped further develop EFS open source mount helpers, efs-utils and efs-csi-driver, using Python

Developed testing infrastructure, including canaries and integration testing, using Python Lambda functions, Typescript with the AWS CDK, and container services along with Kubernetes resources

Led integration efforts with other services within AWS, such as EKS, ECS, EC2, and Lambda

Assisted with automating new region build efforts to make EFS available globally

Implement Deep Convolutional Neural Network using ResNet backbone to identify certain objects within images

Create Synthetic Image Data using Python Script

Assist with communication and coordination with outsourcing partners

Assist with update of Backend Architecture using AWS with Flask Python API

Helped create and process image data using GIMP for the Hopper Algorithm, which creates 3D Models with user taken photos and utilizes Deep Learning techniques