GTM Engineer
Mercor
| Company | Mercor |
| Category | Engineering |
| Location | San Francisco |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | USD 175k–250k |
| Posted | 7 Aug 2026 |
| Last verified | 8 Aug 2026 |
| Source | Employer ATS (ashby) |
Description
ABOUT MERCOR
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
This is a rare, foundational hire: Mercor's first GTM Engineer. You'll sit at the intersection of engineering, growth, and marketing — building the systems that power how Mercor acquires, serves, and expands customers.
You'll design and deploy the infrastructure behind Mercor's go-to-market engine from the ground up: integrating AI agents into customer workflows, building the data and tooling to power marketing and sales, and transforming manual, spreadsheet-driven processes into reliable, production-grade systems.
The ideal candidate combines strong technical depth with exceptional business instincts. You understand how modern go-to-market organizations actually operate — from lead generation and attribution to pipeline management and customer expansion — and have the technical fluency to turn that understanding into scalable systems. You're equally comfortable writing SQL and Python, building AI-powered workflows, and partnering with marketing and revenue leaders to solve high-leverage operational problems.
WHAT YOU'LL DO
GTM DATA & SYSTEMS
- Design, build, and maintain the data and automation infrastructure that powers Mercor's go-to-market organization, spanning marketing, sales, customer success, and operations including account & contact enrichment, and outbound and email tooling
- Partner closely with Marketing, Revenue, Operations, and Engineering to translate business requirements into scalable data models, workflows, and technical systems
- Build and maintain reliable integrations across Mercor's GTM stack (Attio, Customer.io, Clay), ensuring customer, pipeline, and product data remain accurate and accessible
- Develop dashboards, experimentation frameworks, and self-serve reporting that give GTM leaders real-time visibility into pipeline, conversion, attribution, and revenue performance
- Own the quality, documentation, and governance of GTM data so teams can make decisions with confidence
AI & AUTOMATION
- Build AI agents that automate lead research, enrichment, routing, campaign execution, outbound personalization, customer intelligence, and other high-impact workflows
- Deploy production-grade automations using frontier language models, APIs, workflow orchestration, and modern data infrastructure to eliminate manual operational work
- Rapidly prototype AI-powered workflows, measure their business impact, and scale successful experiments into core GTM infrastructure
- Stay at the frontier of AI tooling and proactively introduce new capabilities that increase the leverage of Mercor's go-to-market teams
SCALE & OPERATIONS
- Build reliable, observable data pipelines and workflows that customer-facing teams depend on every day
- Continuously identify operational bottlenecks and automate repetitive processes across the customer lifecycle
- Improve TAM mapping, account and contact enrichment, rules of engagement, attribution, and lead routing — giving decentr