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You will build tools to evaluate agent behavior, analyze traces, and implement features for automatic self-improvement. Additionally, you will run experiments on Mastra primitives to optimize configuration and performance.
We’re looking for an AI engineer. You’ll work on features that help developers understand their agents’ behavior, evaluate their performance, and improve them over time.
This is a hands-on engineering role. You’ll move between experiments, benchmarks, and product code, taking what you learn from evaluating agents and using it to shape the framework.
Why:
We’re starting to build more and more agentic features into Mastra: Trace intelligence, and we’re working on various Agent Learning features to automatically self-improve agents (Autoevals + Suggestions, Rollouts).
In addition, we’ve been increasingly running Mastra primitives like memory on industry-standard benchmarks and using the results to fine-tune configuration.
What you’ll do
Build the features that make this possible: tools for understanding traces, evaluating agent behavior, and turning results into improvements.
Run experiments on Mastra’s primitives, investigate where they perform well and where they fall short, and use those findings to improve their configuration and behavior. You’ll help turn that work into capabilities developers can use in their own applications.
You have:
Shipped agents and agentic applications into production
Tuned and tweaked them to improve accuracy
You need to be able to benchmark your results against existing datasets, or intelligently creating.
Mastra is the open-source TypeScript framework for building AI agents. Built by the team behind Gatsby, backed by Y Combinator and Spark Capital, with $35M raised total. We went from 0 to 27k+ stars and 1M+ weekly npm downloads in under 18 months.
Small team, shipping fast, fully remote. Most of us work across North American and European time zones.
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