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.
About the Role
As a Software Engineer on the Automations team at Mercor, you’ll join a small, high-leverage engineering group building the autonomous systems that run Mercor’s internal operations — and eventually, operations at scale for the companies we serve.
This is not a research role. You’ll design and ship production agents that take real actions: scheduling interventions, executing operational playbooks, managing talent pipelines, and surfacing decisions that previously required hours of manual click-ops. From day one, you’ll own systems end-to-end — from MCP server design to evaluation frameworks — working directly with operators and platform engineers to turn repeatable human workflows into reliable, autonomous ones.
You’ll reason about correctness, rollback, observability, and trust in systems that touch payments, contracts, and people’s livelihoods. This is greenfield agentic infrastructure with immediate real-world impact.
What You’ll Do
Build and maintain MCP servers that give agents structured access to Mercor’s platform reading project state, taking management actions, and triggering communications.
Design and implement evaluation frameworks to measure agent decision quality and drive continuous improvement through feedback loops.
Develop action queues and playbook orchestration systems that allow agents to execute multi-step workflows with conditional logic.
Instrument agent systems end-to-end — capturing outcomes, closing feedback loops, and enabling hill-climbing on eval metrics.
Collaborate directly with operators to identify high-leverage automation opportunities and translate them into robust agent behaviors.
Debug and harden agent systems in production, designing for reliability at scale.
Contribute to foundational patterns and infrastructure that the rest of the company will build on.
What We’re Looking For
Strong backend engineering fundamentals in Python (or equivalent modern language).
Experience building with LLM APIs — including tool use, structured outputs, and multi-step reasoning workflows.
Comfort designing evaluation frameworks and thinking rigorously about agent failure modes.
Ability to ship quickly and iterate on systems that interact with the real world.
Understanding of distributed systems, APIs, and production infrastructure.
Full-stack experience is a plus — owning features end-to-end will increase your impact.
Why Mercor
Impact: Your work powers how the world’s leading AI labs train and test their models.
Learning: Get early insights into frontier model capabilities months before the market.
Growth: Work on both infrastructure and research-adjacent projects with fast paths to ownership.
Benefits
Bi-annual performance bonus structure
Generous equity grant vested over 4 years
Up to $15k Relocation bonus
$10K housing bonus (if you live within 0.5 miles of our office)
$1.5K monthly stipend for meals
Free Equinox membership
$200 monthly laundry reimbursement
$200 monthly personal wellness reimbursement
Health, Dental, Vision insurance
Skills Required
- Strong backend engineering fundamentals in Python or equivalent modern language
- Experience building with LLM APIs including tool use and multi-step reasoning workflows
- Comfort designing evaluation frameworks and thinking rigorously about agent failure modes
- Ability to ship quickly and iterate on systems that interact with the real world
- Understanding of distributed systems, APIs, and production infrastructure
- Full-stack experience is a plus
Mercor Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Mercor and has not been reviewed or approved by Mercor.
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Fair & Transparent Compensation — Pay is considered competitive across many roles, with clear hourly ranges and an hourly/pay‑per‑task mix designed to align rates with expertise. The structure emphasizes transparent, appropriate pay levels and guarantees payment for legitimate logged time.
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Strong & Reliable Incentives — Payments are processed on a predictable weekly cadence via Stripe/Wise, and some tracks offer additional weekly bonus incentives for top performers. This combination of regular payouts and performance bonuses supports dependable earnings when projects are active.
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Equity Value & Accessibility — Select full‑time roles include generous equity grants alongside cash perks such as relocation and housing bonuses. These elements increase total compensation for those positions.
Mercor Insights
What We Do
We use AI to understand human ability and match talent with the opportunities they're best suited for.
