Customer Success Engineer - Fully Remote

mercor; Comisión de Fomento de Perú; Remote; ARS 53,056,000 - 75,794,000; Full time

Job summary

Mercor connects elite creative and technical talent with leading AI research labs. We seek a Customer Success Engineer (LatAm) to support a remote, contract-based role with significant overlap with Pacific Time.

You will debug web applications, assist customers, and surface product risks to our engineering team. Candidate should have strong experience in web stacks (React/Node/Flask/Next.js) and a background in AI systems, LLMs, and AI APIs.

Qualifications

• Ability to debug web applications.
• Degree in Computer Science, Software Engineering, or a related technical field from a top-tier institution or startup experience.
• Experience building modern web applications (React, Node, Flask, Next.js, etc.) OR 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.
• Familiarity with modern AI APIs (OpenAI, Anthropic) or agent frameworks (LangChain, AutoGPT) is a plus.

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.

Skills

Debug web apps

Web development

Customer support

AI systems

LLMs

AI APIs

LangChain

Prompt engineering

Education

CS/Software Eng degree

Tools

React

Node.js

Flask

Next.js

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/year 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.) OR 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.
• Familiarity with modern AI APIs ( OpenAI , Anthropic , etc.) or how agent frameworks ( LangChain , AutoGPT , etc.) function is a plus.