This role is for one of our clients

Compensation: $130 per task

We are 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 our Studio.

Requirements

Key Responsibilities

• 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

Ideal Qualifications

• 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

Working Details

• Fully remote and asynchronous, with expert team leads across US, India, and Nigeria time zones
• Work is performed in our 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

Application Process

• 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

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.