Gen AI Engineer | $70/hr | Remote

AI Engineers, Software Engineers & MCP Evaluation Experts. 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
Who Can Apply
Relevant backgrounds include:
AI Engineers, Software Engineers, Senior Software Engineers, Backend Engineers, Systems Engineers, Platform Engineers, Infrastructure Engineers, Full-Stack Engineers, and Developer Productivity Engineers.
We also welcome:
Machine Learning Engineers, ML Systems Engineers, AI Infrastructure Engineers, Applied AI Engineers, Research Engineers, LLM Engineers, Agent Engineers, and 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, and 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, and Engineering Productivity Engineers.
Additional relevant backgrounds include:
Open Source Engineers, Compiler Engineers, Database Engineers, API Engineers, Integration Engineers, Security Engineers, Networking Engineers, Storage Engineers, and 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
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.

Work arrangement
Yes