3 days ago
Base Salary
$130k - $500k/yr
Responsibilities
- Design, build, and ship backend services and APIs for Mercor’s assessment platform.
- Own features end-to-end from product discussions and technical design through implementation, testing, and release.
- Build evaluation pipelines and data models combining human judgment with AI-powered scoring.
- Develop candidate- and expert-facing assessment product surfaces across the stack.
- Partner with Product, AI, and Data teams to translate assessment research into production systems.
- Use modern AI coding tools to accelerate development while maintaining high engineering standards.
- Improve the performance, reliability, and observability of assessment infrastructure.
- Solve customer problems and improve candidate and expert experience.
Requirements
- 3+ years of professional software engineering experience building production systems.
- Strong backend fundamentals in API design, data modeling, distributed systems, and relational databases.
- Comfort working across the stack with modern frontend frameworks such as React and TypeScript.
- Experience building or integrating LLM-powered production features is preferred.
- Experience using AI development tools such as Cursor, Claude Code, GitHub Copilot, or Codex is preferred.
- Strong software engineering fundamentals, including testing, debugging, and performance optimization.
- Strong product intuition, ownership, curiosity, and adaptability in a fast-moving environment.
Benefits
- Bi-annual performance bonus structure.
- Generous equity grant vested over four years.
- Relocation support.
- Proximity bonus for living near an office.
- Monthly meal stipend.
- Free Equinox membership.
- Monthly laundry reimbursement.
- Monthly personal wellness reimbursement.
- Health, dental, and vision insurance.
- In-person work five days per week in San Francisco, New York City, or London.
Tech Stack
Categories
BackendProduct Engineering
About Mercor
We find the best experts in every professional domain and put their knowledge to work training frontier models. Through APEX, we measure whether those models can actually perform economically valuable work. We're also bringing that expertise to enterprises: deploying custom AI agents, staffing teams with vetted domain experts, and helping organizations encode their own knowledge into AI systems.