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

mercor; San Francisco (CA); Hybrid; CLP 34,247,000 - 48,924,000; Full time

Job summary

Mercor is seeking a Customer Success Engineer (LatAm) to support enterprise clients remotely. You will troubleshoot end-to-end issues, reproduce bugs, and work across our AI+SaaS stack to ensure smooth user experiences.

The role requires a CS-related degree, 2–5 years of customer-facing experience with modern web apps, and comfort with AI systems and agents. This is a remote contract position with overlap in Pacific Time hours.

Qualifications

• Degree in Computer Science, Software Engineering, or related field.
• 2–5 years of experience supporting customers on modern web applications.
• Experience with web stacks: React, Node, Flask, Next.js or similar.
• Familiarity with AI systems, LLMs/agents and generative models.
• Ability to debug end-to-end web applications and understand model outputs.

Responsibilities

• Investigate talent-reported issues end-to-end and reproduce bugs.
• Debug across AI + SaaS stack using telemetry and logs to understand production behavior.
• Triage issues, escalate engineering problems, and provide user guidance.
• Surface systemic patterns and product risks to engineering and leadership.
• Create runbooks and documentation to reduce recurring issues.

Skills

Debug web apps

React

Node

Flask

Next.js

LLMs

AI systems

Agents

Prompt engineering

Education

CS degree or equivalent

Tools

OpenAI APIs

LangChain

Job description

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.