Customer Success Specialist - Fully Remote | Upto $50K/yr
mercor · Remote (45 locations)
Posted January 21, 1970
AI Summary
Mercor is seeking a Customer Success Engineer (LatAm) on a contract basis to investigate and resolve issues reported by talent on its platform. The role involves reproducing bugs, debugging across an AI and SaaS stack, triaging between UX friction, model edge cases, and true system defects, and documenting patterns for engineering and product leadership. It's interesting for engineers who want to combine hands-on web debugging with exposure to LLM behavior and AI tooling.
Job Description
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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