Read more about the research team’s work here: https://decagon.ai/blog/introducing-decagon-labs
The Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments.
Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale.
As a Research Engineer focused on Safety, you’ll be responsible for making Decagon’s AI agents safe, reliable, and controllable, from evaluation through production. You’ll identify real-world failure modes and build the models, evaluations, and safeguards that prevent them.
We’re looking for strong engineers who want to advance applied AI safety in production. People here own their work end-to-end, ship real improvements, and are trusted to make high-impact technical decisions.