Scaled Support Specialist

Diagnose and resolve complex technical issues across OpenRouter's API, spanning multiple LLM providers

Reproduce bugs in ambiguous environments — different SDKs, languages, frameworks, and auth configurations — using tools like curl , Postman, and small test apps

Read and interpret logs, headers, and request traces; identify whether the problem is client-side, OpenRouter-side, or an upstream provider issue vs. a user misconfiguration

Turn "it doesn't work" into actionable findings: exact steps to reproduce, clear hypotheses, and verified fixes or workarounds

Respond to developer inquiries across support channels (email, Discord, GitHub) with clarity, empathy, and technical precision

Translate complex technical root causes into human-friendly explanations

Set expectations on timelines and next steps; provide proactive updates and close the loop

Identify patterns in support requests and advocate internally for documentation improvements, API design changes, or better messages

Stay current with the rapidly evolving LLM ecosystem

Develop deep expertise in OpenRouter's routing logic, fallback behavior, rate limiting, streaming (SSE), and billing systems with minimal hand-holding

Spot systemic issues underneath individual tickets and push for the fix that prevents 50 more

Identify trends in support volume to capture product feedback and inform roadmap priorities

Collaborate on improving the developer experience

4+ years in a technical support, developer support, solutions engineering, or similar role — ideally supporting an API or developer tools product

Exceptional troubleshooting instincts

Strong API fluency

Proficiency in at least one scripting language (Python or TypeScript)

Excellent written communication

Comfort with ambiguity

Genuine passion for AI and LLMs

Familiarity with the OpenAI SDK / Chat Completions API format

Experience with AI/ML frameworks like LangChain, LlamaIndex, or Hugging Face

Experience with observability tools (logging, tracing, metrics)

Experience scaling support operations — e.g., implementing AI-assisted support bots, building internal support dashboards, or creating automated triage workflows

Contributions to open-source projects or developer communities

Background in or exposure to ML/AI concepts beyond just using APIs (benchmarking, evals, fine-tuning)

Work at the center of the AI infrastructure stack as enterprises define how they adopt LLMs.

High ownership and autonomy to define how developer education and community scale.

Opportunity to shape a foundational function at a fast-growing company.

Fully remote team with a culture of autonomy and trust.

Competitive compensation, including base salary and equity.