Summary
Divyansh Agarwal is an applied AI research engineer with 11 years of experience, currently building agentic and production-grade generative AI solutions for CRM and collaboration platforms. A CMU LTI graduate who worked with Prof. Zach Lipton, he has led research and product engineering on factuality, long summarization, RAG systems, LLM creativity, safety post-training, and automated evaluation at Salesforce AI Research. He blends rigorous academic grounding with hands-on production deployments—shipping models integrated with Slack, Tableau, and Einstein Trust Layer—and now continues applied AI work at Scale AI. Beyond models, he has experience designing synthetic RL simulation environments and human-in-the-loop annotation pipelines, reflecting a systems-minded approach to trusted AI. Notably, his background spans industry research, internship experience at Uber, and international research collaborations, giving him a breadth of perspective across applied NLP and ML engineering.
11 years of coding experience
8 years of employment as a software developer
Bachelor of Engineering (BE) Information Technology, Bachelor of Engineering (BE) Information Technology at Netaji Subhas Institute of Technology
Master's degree Computational Data Science, Master's degree Computational Data Science at Carnegie Mellon University