Mercor is seeking experienced Go engineers to build the dataset that teaches AI agents to reason about real codebases.
Codebase Q&A is a reinforcement-learning environment for training AI agents to explore and reason about software repositories they have never seen before. You will build difficult codebase-exploration tasks: high-level engineering questions about production Go repositories that cannot be answered by reading a single file, and that require runtime evidence to resolve — the kind of question a senior engineer answers by actually investigating the system.
This track works on infrastructure-grade Go codebases including etcd, Traefik, Helm, Kustomize, CoreDNS, NATS Server, Temporal, Syncthing, restic, Authelia, BadgerDB, quic-go, gRPC-Go, Hugo, rclone, Trivy, cert-manager and Pion WebRTC.
Contract, task-based work paid at $130 per approved task, performed remotely in Mercor Studio.
Select tasks from a pre-validated pool of Go repositories, each pinned to a specific git commit and arriving with an engineering question, positive and negative rubrics, foils, and a golden solution
Explore the repository until you genuinely understand the subsystem in question, including the relevant PR or issue history
Rewrite the task's question so it defeats frontier coding agents while remaining well-defined and fairly answerable
Adjust rubrics and foils so they reward correct reasoning and reject plausible-but-wrong answers
Run the full validation loop in Studio — Check, Golden, Run, Analyze — and iterate until every stage passes
Document your work in the task README and submit for expert review, addressing reviewer feedback on returned tasks
3+ years of professional software engineering experience, with substantial production Go
Demonstrated ability to navigate a large, unfamiliar Go codebase and explain how it behaves at runtime — not just what the source says
Fluency in Go concurrency, interfaces, module boundaries, and the standard library; comfort reading generated code and build tooling
Experience with distributed systems, networking, storage engines, or Kubernetes-ecosystem tooling is highly relevant — the task mix is weighted toward architecture and system design (42%), code onboarding (26%) and root-cause analysis (20%)
Precise written English: the questions and rubrics you write are the product
Comfortable with git at commit level, containerized environments, and command-line tooling
Fully remote and asynchronous, with expert team leads across US, India, and Nigeria time zones
Work is performed in Mercor Studio; time is tracked with Insightful, and platform access is provisioned through Okta
Onboarding requires identity verification, a background check, signed Terms of Work and CIIAA, a tax form, and passing a short calibration quiz before task access is granted
Payment is per approved task; every task is reviewed by a second engineer and a super reviewer before acceptance
Submit your resume or relevant technical background to get started
Qualified applicants may be asked to complete a brief technical assessment or provide additional information