Staff Backend Engineer — Agentic Systems

Mercor

San Francisco (CA)

On-site

USD 180,000 - 260,000

Full time

13 days ago
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Benefits offered by this job

Generous equity
Relocation bonus
Housing bonus
Meal stipend
Equinox membership
Health insurance

Job summary

Mercor in San Francisco is seeking a Member of Technical Staff on Talent Experience to build the backend systems and agent infrastructure behind every journey in Mercor's talent network. A growing share of Mercor's core work runs on agents that source, screen, match, and support experts with minimal human intervention.

You will design and ship the services those agents run on, including orchestration, tool interfaces, evaluation and guardrails, and scalable data models.

Qualifications

  • 5+ years of professional backend engineering experience.
  • Strong fundamentals in distributed systems and API design.
  • Hands-on experience with LLMs in production or quick learner.

Responsibilities

  • Design, build, and own backend services powering Mercor's agentic workflows.
  • Ship agents into production and iterate with real usage.
  • Build evaluation infrastructure and ensure auditability of agent decisions.
  • Design scalable data models and APIs for a growing talent network.
  • Make agent decisions observable, auditable, and reversible.
  • Collaborate with product, operations, and AI researchers to balance automation and human input.
  • Establish backend engineering standards and raise technical bar.

Skills

Backend engineering
Distributed systems
LLMs in production
API design
Ownership

Job description

Mercor in San Francisco is seeking a Member of Technical Staff on Talent Experience to build the backend systems and agent infrastructure behind every journey in Mercor's talent network. A growing share of Mercor's core work runs on agents that source, screen, match, and support experts with minimal human intervention.

You will design and ship the services those agents run on, including orchestration, tool interfaces, evaluation and guardrails, and scalable data models.

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