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

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)

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Originally posted on Himalayas