Scaled Support Specialist

Role overview

Help developers resolve difficult integration issues with APIs that connect applications to large language models from multiple providers. This is a hands-on support role combining technical investigation, clear communication, and feedback to product and engineering teams; many cases will require independent diagnosis without an established playbook.

Responsibilities - Investigate API issues across model providers, distinguishing client configuration, platform behavior, and upstream service problems. - Reproduce bugs across SDKs, languages, frameworks, and authentication setups using tools such as curl, Postman, or small test applications. - Inspect logs, headers, and request traces, then document reproduction steps, hypotheses, and confirmed fixes or workarounds. - Respond to developer questions across support channels with accurate, empathetic explanations and timely updates. - Identify recurring issues and advocate for improvements to documentation, API behavior, and error messages. - Share support trends and systemic problems with product and engineering, and build expertise in routing, fallbacks, rate limits, streaming, and billing.

Requirements - Four or more years in technical support, developer support, solutions engineering, or a related role; API or developer-tool support is especially relevant. - Strong API knowledge and exceptional troubleshooting skills. - Proficiency in Python or TypeScript. - Excellent written communication and the ability to explain technical causes in accessible language. - Comfort investigating unfamiliar problems with incomplete information, plus a strong interest in AI and language models.

Nice to have - Familiarity with the OpenAI SDK or Chat Completions API format. - Experience with frameworks such as LangChain, LlamaIndex, or Hugging Face, or with observability tools for logs, traces, and metrics. - Experience improving support operations through automation, dashboards, or AI-assisted workflows. - Open-source or developer-community contributions, or knowledge of AI/ML topics such as benchmarking, evaluation, or fine-tuning.