The Ai Training Company
AI Engineer | $100/hr | Remote
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Remote AI Project
We are seeking experienced AI Engineers, Software Engineers, Systems Engineers, Backend Engineers, ML Engineers, and Developer Tooling Experts to build reinforcement learning environments that test how advanced AI models solve complex software engineering problems using Model Context Protocol (MCP) tools.
The core of the role is strong software engineering. Prior professional AI experience is helpful but not required.
What You’ll Do
- Build reinforcement learning environments for software engineering tasks
- Design realistic coding problems based on production-style codebases
- Create tasks involving bug fixing, feature implementation, refactoring, and optimization
- Require AI agents to discover information using real MCP tools and servers
- Design scenarios where agents must inspect repositories, documentation, APIs, databases, logs, or other connected systems
- Create deterministic verification systems that accurately determine whether a solution is correct
- Build automated tests and graders for coding tasks
- Develop golden reference solutions
- Define clear success and failure conditions
- Ensure environments are reproducible across repeated runs
- Identify shortcuts or unintended ways agents could bypass task requirements
- Test whether tasks measure genuine software engineering ability
- Evaluate model behavior when using MCP tools
- Debug environment, tooling, and infrastructure issues
- Improve task difficulty, realism, and evaluation reliability
- Document environment behavior, requirements, and expected solutions
- Collaborate asynchronously with engineers, researchers, and reviewers
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Who Can Apply
Relevant backgrounds include:
- AI Engineers
- Software Engineers
- Senior Software Engineers
- Backend Engineers
- Systems Engineers
- Platform Engineers
- Infrastructure Engineers
- Full-Stack Engineers
- Developer Productivity Engineers
We also welcome:
- Machine Learning Engineers
- ML Systems Engineers
- AI Infrastructure Engineers
- Applied AI Engineers
- Research Engineers
- LLM Engineers
- Agent Engineers
- AI Platform Engineers with strong software engineering fundamentals
Systems and infrastructure backgrounds may include:
- Distributed Systems Engineers
- Cloud Engineers
- DevOps Engineers
- Site Reliability Engineers
- Production Engineers
- Performance Engineers
- Reliability Engineers
- Infrastructure Software Engineers
Developer tooling backgrounds may include:
- Developer Tools Engineers
- Build Engineers
- CI/CD Engineers
- Release Engineers
- Test Infrastructure Engineers
- Automation Engineers
- Internal Tools Engineers
- Engineering Productivity Engineers
Additional relevant backgrounds include:
- Open Source Engineers
- Compiler Engineers
- Database Engineers
- API Engineers
- Integration Engineers
- Security Engineers
- Networking Engineers
- Storage Engineers
- Runtime Engineers with strong coding and debugging experience
Requirements
- Strong professional software engineering experience
- Proficiency in at least one of C++, Python, Java, Go, TypeScript, or Rust
- Deep understanding of algorithms and data structures
- Strong debugging skills
- Experience implementing production software features
- Experience refactoring existing codebases
- Ability to optimize software for performance and scalability
- Strong understanding of testing and verification
- Ability to work effectively in unfamiliar codebases
- Excellent written and verbal communication
- Strong attention to detail
- Ability to work independently in a remote environment
- Experience collaborating across engineering teams
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Preferred Background
- Experience working on large-scale or distributed software systems
- Experience with MCP, tool calling, agents, or AI coding systems
- Experience building developer tools or automation infrastructure
- Experience creating coding benchmarks or evaluation environments
- Experience building automated graders
- Experience with sandboxing or containerized environments
- Experience designing deterministic tests
- Experience with performance engineering
- Experience working on open-source projects
- Experience reviewing complex pull requests
- Experience maintaining large production codebases
- Familiarity with machine learning or AI systems
- Experience creating engineering best practices or technical standards
This opportunity is ideal for engineers who can take a real software engineering problem and turn it into a reproducible, challenging, automatically verifiable environment that tests whether an AI agent can actually debug, reason, use MCP tools, and modify a complex codebase correctly. We are a referral partner of the client.
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