The opportunity
The LangSmith Engine team is building a proactive agent engineer that analyzes production traces, identifies important failures, recommends and writes fixes, and helps prevent those issues from coming back. We’re building agents that can understand complex software systems and…
What you'll do
Build and maintain benchmarks and evaluations that measure the quality and: efficiency of Engine agents on real-world tasks.
Design and run experiments to improve agent performance across models,: prompting, context, tools, orchestration, and agent strategies .
Explore and implement post-training and fine-tuning techniques when they can: meaningfully improve agent capabilities, quality, or cost.
Turn successful experiments into production improvements , working closely: with engineers and researchers to measure impact and prevent regressions.
Help define the ML roadmap and technical direction for improving Engine: agents, and mentor other engineers through strong technical leadership.
+ years of experience in ML/AI research, or a closely related field.
What they're looking for
- Master’s or Ph.D. in a relevant scientific field.
- Hands-on experience working with LLMs and AI agents , including analyzing: model behavior and improving real-world performance
- Strong experience designing benchmarks, evaluations, and experiments for: AI/ML systems; you know how to tell whether a change actually made an agent better.
- Strong software engineering skills, with a track record of taking ideas from: research prototype to measurable production impact .
