AI Engineer, Post-Training & Evaluation

Coval builds an evaluation platform for conversational AI that helps enterprise teams simulate, monitor, and improve voice and chat agents. The AI Engineer owns model development for Coval’s judges, designing and shipping evaluations, improving reliability, and using post-training and other capability work to improve evaluation quality.

Responsibilities:

• Design and ship the LLM judges that score conversations: rubrics, judge prompting, and calibration against human raters
• Build the reliability tracking that keeps judges honest from release to release
• Run post-training where training beats prompting: LoRA adapters on open-weight models, trained on data distilled from our own scored conversations
• Everywhere else, do the non-tuning capability work: tool use, structured outputs, and context engineering
• Keep asking which lever actually moves the metric, and focus there