
Customer Success Engineer - Fully Remote
mercor
customer-success-engineering
technical-support
customer-success
software-engineering
technical-customer-success
remote-customer-success-engineer
customer-success-engineer
technical-customer-success-engineer
senior-customer-success-engineer
cloud-customer-success-engineer
ai
saas
react
nodejs
flask
nextjs
Job details
- Company
- mercor
- Location
- Ecuador
- Remote
- Yes
- Salary
- $35,000 - $50,000
- Field
- Customer Support
- Source
- via Himalayas
Posted
July 22, 2026
About this role
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.
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: https://talent.docs.mercor.com/welcome
- For any help or support, reach out to: support@mercor.com
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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