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Braintrust is looking for Developer Support Engineers to help developers building LLM-powered applications overcome challenging technical blockers and move faster. The goal is to provide surprisingly good developer support as a strategic advantage by helping customers understand and improve AI behavior in production.

Requirements

• Can write, debug, and reason through Python and/or TypeScript codebases.
• Are comfortable learning and reasoning about APIs, SDKs, and developer tools quickly.
• Experience supporting developer tools, ML infrastructure, or observability platforms.
• Familiarity with OpenAI, Anthropic, or similar LLM APIs.
• Comfort working with datasets, evaluation metrics, or prompt engineering.
• Have submitted PRs to production codebases to fix customer-impacting issues in backend services, SDKs, or infrastructure.
• Hold cloud certifications or equivalent experience troubleshooting containerized environments (e.g., Terraform, Kubernetes).

Responsibilities

• Diagnose, troubleshoot, and resolve API and SDK use issues alongside customers codebases (Python or TypeScript).
• Reproduce customer-reported bugs, identify likely causes in our codebase, and collaborate with Engineering to resolve them.
• Own support communications with developers using Braintrust — primarily via Slack and email — and build trust through clear, technical, and empathetic communication.
• Write and maintain knowledge base documentation that turns unknowns into knowns, unblocking future developers.
• Identify opportunities to improve the developer experience, including tools, documentation, and support workflows.
• Write scripts, fix bugs, and contribute to internal tooling that enhances the support process.
• Capture and relay customer feedback to Product and Engineering, helping shape roadmap priorities.

Other

• Have 3-8+ years of experience supporting developer-facing products as a Support Engineer, Developer Success Engineer, Technical Account Manager, or similar technical post-sales role.
• Take personal ownership of technical problems and follow through until customers are unblocked.
• Communicate clearly, empathetically, and effectively — especially when explaining complex or confusing issues.
• Are insatiably curious about use cases for LLMs and excited to support tools that make AI more measurable, reliable, and trustworthy.
• Preferred locations are San Francisco and New York City metro areas for hybrid in person collaboration, but can be flexible for experienced candidates open to working pacific or eastern hours.