[Hiring] Member of Technical Staff @Mercor

Role Description

AI agents need realistic places to practice before they can perform useful work. You will build those environments and the infrastructure that makes them reliable.

This is an applied engineering role. You will own production software from an initial specification through implementation, testing, and delivery. The work changes with the needs of AI labs, so you should be comfortable learning unfamiliar domains and moving quickly without sacrificing technical quality.

What You'll Do

• Build environments end to end.
• Create high-fidelity applications that reproduce the behavior and workflows of professional software.
• Make environments operable by agents.
• Build tool APIs, MCP servers, containerized computer-use systems, and the infrastructure that connects an environment to an agent.
• Create and calibrate tasks.
• Design realistic problems, analyze rollouts, tune difficulty, and determine whether failures come from the model, the task, or the environment.
• Design realistic data.
• Build schemas, large corpora, anonymization pipelines, and fast search and loading systems.
• Improve shared engineering infrastructure.
• Build automation, QA systems, deployment tooling, and workflows used across the team.

Qualifications

• Strong Python skills with enough range across backend, frontend, data, and infrastructure to build a complete application.
• Experience owning technically substantial projects, preferably from an early stage through production.
• Clear, structured communication. You can make a complex system understandable and answer technical questions directly.
• Technical depth. You understand why a system works, how its components interact, and where it can fail.
• Good judgment about architecture, tradeoffs, testing, reliability, and scope.
• Comfort working with changing requirements, close deadlines, and unfamiliar problem spaces.

How We Work

• The India team works remotely with time overlap with New York.
• Engineers own outcomes, communicate risks early, and unblock themselves.
• Specifications may be incomplete. You are expected to clarify what matters, make sound decisions, and carry work through delivery.
• We value practical depth over impressive terminology and working software over unnecessary complexity.

Compensation

• $80,000 - $150,000 (USD)
• Mercor Equity

Interview Process

• Application review: We review your experience and project work for evidence of relevant engineering depth.
• Round 1: Sixty (60) minutes with an engineer, focusing on communication and a technical deep dive.
• Choose the technically strongest system you personally helped build. You will walk through the problem, architecture, your contribution, important decisions, tradeoffs, failures, testing, and what you would redesign today. You may use a whiteboard or diagramming tool.
• Round 2: Hackathon - take-home build expected to take 6 to 8 hours, with a maximum of 8 hours.
• You will receive a detailed brief and supporting materials. We assess the functionality of the result, technical decisions, code quality, testing, reliability, scope management, and your understanding of what you built. AI use is allowed.
• Both interview rounds are eliminatory. Candidates who pass the hackathon proceed to the final hiring decision.

How to Prepare

• For Round 1, choose one project that:
• You know the technical details in depth.
• Shows your personal contribution clearly.
• Includes meaningful architecture or implementation decisions.
• Gives you examples of tradeoffs, failures, debugging, testing, and lessons learned.
• Be ready to diagram the system and trace a request or unit of data through it. Clear reasoning and honest acknowledgment of uncertainty are more useful than rehearsed answers.

Contact

For any questions/information reach out to [email protected] / [email protected]