About the Role Join an AI/ML team building tools to make production AI agents more reliable. You will own the intelligence that identifies agent failures, assesses confidence, and checks whether proposed fixes work. What You'll Do • Detect subtle failures, including omissions, compliant but incorrect responses, and patterns that emerge across large volumes of traces. • Turn user behavior signals, such as rephrasing, abandonment, and retries, into evidence of agent failures. • Build evaluation methods to measure detection precision when labeled ground truth is limited or unavailable. • Make patch generation trustworthy by reproducing failures, verifying proposed fixes, and avoiding low-confidence changes. • Improve the cost efficiency of detection, choosing appropriate models and approaches for each event. • Review production customer traces regularly to identify problems and opportunities for improvement. What We're Looking For • Demonstrated AI/ML engineering experience; candidates with 0 to 10 years of experience are welcome, including new graduates and people without a traditional degree. • Hands-on experience using LLMs in production, including evaluations, LLM-as-judge, embeddings, and deciding when a smaller model or no model is appropriate. • An individual-contributor engineering background and a track record of shipping products that people use. • Strong research judgment and the ability to distinguish meaningful improvements from noise, especially when ground truth is unavailable. • Experience running agents in production and learning from their failures is a plus. Compensation & Benefits Base salary: $120,000 to $200,000 annually. Visa sponsorship is not available. Location On-site in San Francisco, United States.