About the job
About braintrust
Braintrust is at the forefront of AI observability, merging evaluation and observability into a seamless workflow. Our platform empowers developers to gain critical insights into AI behavior in production environments and provides tools for optimization.
Renowned companies such as Notion, Stripe, Zapier, Vercel, and Ramp leverage Braintrust to assess models, test prompts, and identify regressions, transforming production data into enhanced AI performance with each update.
About the Role
We are seeking a passionate Backend Engineer to contribute to the foundational infrastructure of innovative AI development tools.
Braintrust operates as a real-time, highly available data platform within both SaaS and self-hosted ecosystems. Your contributions will be pivotal in scaling our data ingestion pipelines, enhancing our open-source libraries, and ensuring optimal system performance and reliability. If you excel in a dynamic environment and relish tackling complex systems challenges with a product-oriented mindset, we would love to collaborate with you.
Your Responsibilities
As a Backend Engineer at Braintrust, you will play a key role in shaping the core platform that facilitates LLM-native development:
Design and deploy features that provide users with profound insights into their LLM utilization and performance metrics.
Integrate, proxy, cache, and aggregate data from leading model providers such as OpenAI, Anthropic, and Gemini, which our clients depend on.
Create and refine robust, efficient open-source libraries for tracing and evaluating LLM calls within client applications. Explore our SDKs
Develop highly available real-time data pipelines to ingest, store, and query extensive volumes of structured and semi-structured AI usage data.
You will also collaborate closely with product engineers to deliver polished, comprehensive features that address real customer challenges, including:
Bundling and uploading JavaScript and Python code snippets for on-demand function calls in LLM workflows.
Facilitating the parsing and uploading of attachments from LLM multimodal outputs for long-term storage.
Implementing role-based access controls and data retention protocols for enterprise scenarios.

