I'm a Principal Applied Scientist at AWS who builds AI services like Amazon Bedrock and Lex. AMA! [D]
James Gung, a Principal Applied Scientist at AWS, joined Amazon in 2021 and has since contributed to AI services such as Lex, Bedrock, Q Business, and Amazon Quick. His research focuses on areas including task-oriented dialogue, agent evaluation, conversation simulation, and proactive agents. He recently participated in an AMA on r/MachineLearning.
This AMA offers a rare direct insight into the development process and research priorities for Amazon's AI services like Bedrock and Lex, unlike typical product announcements.
Time & source
Times shown in UTC
Display time zone: UTC
Local time zone unavailable; showing UTC.
PublishedOffset at this time: UTC+0Sep 18, 2026, 16:13 UTC
IngestedOffset at this time: UTC+0Sep 18, 2026, 18:00 UTC
- Published
- Sep 18, 2026, 16:13
- Ingested
- Sep 18, 2026, 18:00
- Source type
- Dev community
- Tier
- Community
- Source status
- Healthy
Tier is a per-source editorial setting, not a per-item score.
Discussion trend
The percentage is based on collected discussion signal, not new comments or independent people. The curve only compares the same topic across time.
Hi r/MachineLearning! I'm James Gung, a principal applied scientist at AWS. I joined Amazon in 2021 and have since worked on AI services like Lex, Bedrock, Q Business, and Amazon Quick (an AI assistant for work). In that time, I've done research on topics like task-oriented dialogue, agent evaluation, conversation simulation, and proactive agents.
Before AWS, I worked on conversational AI systems at Amelia and did my PhD in Computer Science at the University of Colorado Boulder.
Feel free to ask about my career path, internships, interviews, or what it's like day to day as an applied scientist at Amazon. Outside work, I like to play violin, go bouldering, travel with my wife, and hang out with our two dogs. Ask me anything!
*Disclaimer* I'm speaking from personal experience here, not as an official Amazon spokesperson. I can't discuss unannounced products, financials, competitors, internal tools, legal matters, pricing, or customer data - but pretty much everything else about my career, research, and life as an applied scientist is fair game. Let's go! 🧠