Customer Success Engineer (India)

Mercor’s Talent Success team is hiring! Our Talent Success team is responsible for ensuring everyone using our platform has a delightful experience end to end, from applying to job listings, taking our AI-led interviews, accepting offers on our platform, and getting paid for their hard work.

Mercor has thousands of users joining the platform each week to interview for different roles our clients have posted. When they run into issues or have questions and reach out for help, you will be responsible for giving them a speedy and delightful experience.

Location Requirements

Mercor’s Talent Success team is hiring! Our Talent Success team is responsible for ensuring everyone using our platform has a delightful experience end to end, from applying to job listings, taking our AI-led interviews, accepting offers on our platform, and getting paid for their hard work.

Customer Success Engineer (India)

$20K-$35K / yr

$20K-$35K

About the Role

Mercor has thousands of users joining the platform each week to interview for different roles our clients have posted. When they run into issues or have questions and reach out for help, you will be responsible for giving them a speedy and delightful experience. You will work directly with our engineering team, triaging and investigating bug reports so being super savvy with modern websites and issues SaaS-type applications run into will come in handy. Since your conversations with the talent applying on our platform will often be the first interaction someone has with Mercor, maintaining an enthusiastic, upbeat tone while writing at native English level proficiency is important. We use a lighthearted and informal tone in our support communication while at the same time being very professional and precise in our replies.

Key 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.

• 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

Ability to debug web applications, likely coming from either a 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 — you’ve played 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 how modern AI APIs work (OpenAI, Anthropic, etc.) or how agent frameworks (LangChain, AutoGPT, etc.) function is a plus. Mercor is at the intersection of labor markets and AI research. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development. Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request. Posted 10 months ago

• Ability to debug web applications, likely coming from either a

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 — you’ve played 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 how modern AI APIs work (OpenAI, Anthropic, etc.) or how agent frameworks (LangChain, AutoGPT, etc.) function is a plus.

• 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 — you’ve played 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 how modern AI APIs work (OpenAI, Anthropic, etc.) or how agent frameworks (LangChain, AutoGPT, etc.) function is a plus.