Mercor

Mercor

Fullstack Software Engineer, Agent Platform

San Francisco · Mid

Sponsorship not specifiedDetected 66 days ago
JavaScriptTypeScriptPythonReactNext.jsNode.jsBackend DevelopmentFull-Stack DevelopmentRESTLLMsAgentic AIDesign SystemsCommunicationCollaboration

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40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • It is simultaneously our internal workbench and our external storefront.
  • You'll be directly responsible for the enablement of hundreds of internal users who depend on the platform daily, and dozens of enterprise clients who run on it in production.
  • This is a role for someone who cares equally about engineering craft and product impact: shipping scalable, reliable systems and intuitive interfaces that make everyone who touches the platform faster and more effective.

Responsibilities

  • Own the agent platform across the full stack - from the internal- and client-facing React interfaces to the backend APIs and services orchestrating agents, workflows, and integrations.
  • Build the foundational layer other teams depend on to stand up new agent use cases, task formats, and client configurations quickly and without rework.
  • Translate ambiguous requirements into well-scoped technical solutions through close collaboration with Applied AI researchers, product, design, and operations.
  • The platform you build is Mercor's core agent product - run internally and shown to every enterprise client.
  • As a Full Stack Software Engineer on the Agent Platform team, you'll own these journeys end-to-end: the React frontend people interact with and the backend services that orchestrate agents, data, and integrations.

Requirements

  • Deep proficiency in JavaScript/TypeScript (React + Next.js) and a strong grasp of frontend architecture, state management, and design patterns.
  • Experience with complex, high-throughput systems - pipelines, large data volumes, or multi-tenant architectures.
  • Strong communication skills and ability to articulate technical and product tradeoffs clearly.
  • Experience at top-tier tech companies or fast-scaling startups.

Compensation

  • Bi-annual performance bonus structure

Benefits

  • Bi-annual performance bonus structure
  • Generous equity grant vested over 4 years
  • Up to $15k Relocation bonus
  • $10K proximity bonus (if you live within 0.5 miles of our office)
  • $1.5K monthly stipend for meals
  • $200 monthly laundry reimbursement
  • $200 monthly personal wellness reimbursement
  • Health, Dental, Vision insurance

Company info

  • Mercor's mission is to organize human intelligence to power the AI economy.
  • We're a leading AI data company, building the layer between human expertise and frontier models.
  • Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models.
  • Mercor's APEX benchmark family measures AI's real-world impact on professional work.
  • Mercor Enterprise brings this same infrastructure to Fortune 500 companies:
  • helping companies capture how their best people actually work, translating that expertise directly back into agents.
  • 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 work in-person five days a week in our San Francisco, NYC, or London offices.
  • Your work directly shapes both how Mercor works and how customers experience us.
  • Our agent platform is the core system Mercor uses to build, run, and showcase AI agents - the same platform our teams rely on internally every day and the one we demo live on customer calls.
  • Because what you build is used in-house and demoed to customers, it has to be both genuinely powerful and demo-ready polished.

This listing is sourced directly from Mercor's careers page and normalized into a canonical job model.