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Mercor

Automates candidate screening and matching

Software Engineer - Agents

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$160k - $500k /yr

About the Job

Responsibilities

  • Own agentic features end-to-end, from scoping with researchers and operations partners through implementation, launch, and iteration based on customer feedback.
  • Design and ship large language model agents, harnesses, and verifiers, including the tools, prompts, and policies needed for reliability.
  • Build Python/FastAPI services and Temporal/Modal pipelines to orchestrate agent runs and human-in-the-loop review and iterations.
  • Build reinforcement learning environments for frontier agents, including realistic enterprise applications, simulated coworkers, and company data rooms supporting tasks that span hours to days.
  • Build tooling to turn agent trajectories into insights, including statistical analysis and automated failure-mode detection.
  • Build and refine full-stack interfaces and data infrastructure, including Next.js/React interfaces and data models providing agents structured context and audit trails.
  • Define agent quality and drive continuous improvement by building evaluations, instrumenting traces, analyzing failure modes, and iterating on prompts, tools, and guardrails to improve reliability, cost, latency, and user experience.
  • Partner with Product, Design, Research, and Operations to shape agent autonomy and determine appropriate autonomous actions, propose-and-approve flows, and human-in-the-loop decisions.

About the Company

Mercor

Automates candidate screening and matching

Mercor provides an AI-driven recruitment platform that automates key parts of hiring for both job seekers and employers. Job seekers upload their CVs and complete a 20-minute AI-led video interview, after which a proprietary language model generates detailed candidate profiles; employers receive automated resume screening, candidate matching, and initial interviews, with tailored AI interviews for specialized roles. The system uses a company-trained model to rank and recommend candidates by qualifications and predicted performance, and operates on a finder’s-fee revenue model with large-scale usage across software, operations, design, and other fields, including AI labs. Its goal is to speed up hiring while reducing bias and delivering better job-to-citizen matches.

Company size
201-500
Company stage
Series C
Total funding
$483.6M
Headquarters
Menlo Park, CA
Founded
2023

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