Customer Success Specialist - Fully Remote | Upto $50K/yr

🏢 mercor · all mercor jobs
📍 Costa Rica
💰 USD 35,000 - 50,000 / annual
📅 Posted 2026-08-30 · via Himalayas
🏷 Customer-Success-Engineer,Technical-Customer-Success,AI-Customer-Support,Customer-Support-Engineer,Technical-Support-Engineer,Remote-Client-Success-Specialist,Customer-Success-Specialist,Client-Success-Specialist
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About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .

Position: Customer Success Engineer (LatAm)
Type: Contract
Compensation: $35,000–$50,000
Location: Remote
Commitment: Substantial overlap with Pacific Time (PT/PST)
Role Responsibilities

- Investigate talent-reported issues end-to-end. Reproduce bugs, identify root causes, and separate UX friction, model edge cases, and system defects.

- Debug across our AI + SaaS stack using telemetry, logs, network inspection, and database queries to understand production behavior.

- Triage with sound judgment. Escalate true engineering issues and resolve others via configuration, prompt refinement, or clear user guidance.

- Surface systemic patterns and product risks to engineering and product leadership.

- Create clear documentation and runbooks to reduce repeat issues and improve resolution speed.

- Communicate with precision, professionalism, and empathy.

Qualifications

Must-Have

- Ability to debug web applications.

- Degree in Computer Science, Software Engineering , or a related technical field from a top-tier institution or prior experience at a high-growth technology startup.

- Experience building modern web applications ( React , Node , Flask , Next.js , etc.).

- 2–5 years of experience supporting customers on such web applications.

- Comfortable with AI systems . Experience with LLMs , agents, or generative models.

- Experience exploring behavior of AI tools (fine-tuning, prompt chains, chain-of-thought debugging, or building agents).

- Ability to understand model outputs, failure modes, hallucinations, and feedback loops.

Preferred
- Familiarity with how modern AI APIs work ( OpenAI , Anthropic , etc.) or how agent frameworks ( LangChain , AutoGPT , etc.) function.

Application Process (Takes 20–30 mins to complete)

- Upload resume

- AI interview based on your resume

- Submit form

Resources & Support

- For details about the interview process and platform information, please check:

- For any help or support, reach out to:

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Originally posted on Himalayas

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