Software Development Engineer at Amazon building Alexa's personality and emotional intelligence with LLMs, RAG systems, and prompt engineering.
I'm a Software Development Engineer II at Amazon, where I work on Alexa's personality and emotional intelligence. I design and build systems that make AI assistants more human — from emotional understanding through audio sentiment analysis to RAG-powered personality retrieval.
My work spans the full stack of modern AI engineering: LLM evaluation platforms, retrieval-augmented generation, prompt engineering, and building production systems that serve millions of users daily.
I hold a Master's in Computer Science from Indiana University Bloomington and am an AWS Certified Cloud Practitioner. I'm passionate about leveraging AI-assisted development tools to push the boundaries of what's possible.
Serverless platform that benchmarks Alexa+ response quality across 1M+ prompts using an automated "LLM-as-a-Judge" scoring system and a low-code UI for cross-functional science teams.
Sarcasm detection system combining audio sentiment analysis with lexical text scoring. Triggers dynamic prompt injection for context-aware empathetic responses when sarcasm is detected.
Converts user utterances into dimensional vectors for OpenSearch k-NN queries, deterministically overriding parametric LLM generation for 100% consistency on immutable personality traits.
Microservices-based architecture displaying atmospheric charts from NEXRAD and NASA MERRA-2 satellite data. Stress-tested to handle thousands of requests per minute at 95% success rate.
I'm always open to discussing new opportunities, interesting projects, or just having a great conversation about AI and engineering.