AI Engineer | $100/hr | Remote

We need to output HTML fragment with sections: About the role (maybe), Responsibilities, Requirements, Qualifications? The posting includes "What You’ll Do" (responsibilities), "Who Can Apply" (maybe qualifications), "Requirements", "Preferred Background". Also maybe "Benefits", "Pay", "Schedule" not present, so we omit those sections. Also need to include section headings using

. Use

• for any list of duties/requirements/benefits. Use

  for prose. We must not repeat job title as heading. No Job ID etc. Remove boilerplate. Preserve all substantive info. We need to decide sections: About the role (maybe intro paragraph), Responsibilities (What You’ll Do), Requirements (Requirements), Preferred Background (maybe Qualifications or Preferred Background). Could also have "Who Can Apply" as Qualifications. The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can use About the role, Responsibilities, Requirements, Qualifications. Possibly Skills not needed. We need to ensure we only include sections when posting has real specific content. We have content for About the role (intro paragraph), Responsibilities (What You’ll Do), Requirements (Requirements), Qualifications (Who Can Apply + Preferred Background maybe). Could combine Who Can Apply and Preferred Background into Qualifications. We must not invent or summarize away detail. Must preserve all substantive info. So we need to include all bullet points from responsibilities, requirements, who can apply, preferred background. We need to format lists with

  • . For prose paragraphs use

    . We need to avoid duplication. The posting includes many bullet-like sentences separated by line breaks. We'll convert each line into

  • . Let's extract: Intro paragraph: "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." That's About the role. Responsibilities (What You’ll Do): list items: - 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 Requirements (Requirements): list: - 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 (Preferred Background): list: - 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 Who Can Apply (maybe Qualifications): list of relevant backgrounds. That's a long list. We need to preserve all substantive info. So we need to include that as part of Qualifications. Could be a paragraph summarizing? But we must not invent or summarize away detail. We could list each background as
  • . That would be huge but okay. The "Who Can Apply" section includes many bullet-like items separated by commas and "and". We need to parse them into list items. Let's extract the list: "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." We need to preserve all these. We'll create a list of each role. Let's split by commas and "and". We'll produce items: - AI Engineers - Software Engineers - Senior Software Engineers - Backend Engineers - Systems Engineers - Platform Engineers - Infrastructure Engineers - Full-Stack Engineers - Developer Productivity Engineers - 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) maybe note that phrase but we can keep as is. - Distributed Systems Engineers - Cloud Engineers - DevOps Engineers - Site Reliability Engineers - Production Engineers - Performance Engineers - Reliability Engineers - Infrastructure Software Engineers - Developer Tools Engineers - Build Engineers - CI/CD Engineers - Release Engineers - Test Infrastructure Engineers - Automation Engineers - Internal Tools Engineers - Engineering Productivity Engineers - Open Source Engineers - Compiler Engineers - Database Engineers - API Engineers - Integration Engineers - Security Engineers - Networking Engineers? Actually "Networking Engineers" - Storage Engineers - Runtime Engineers (with strong coding and debugging experience) We need to keep the qualifiers like "with strong software engineering fundamentals" and "with strong coding and debugging experience". We'll include them as part of the item text. Now we need to decide sections: About the role (intro paragraph), Responsibilities, Requirements, Qualifications (Who Can Apply), maybe Preferred Background as separate section? Could combine Preferred Background into Qualifications as a subsection? But instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can have Qualifications heading and include both Who Can Apply and Preferred Background as list items under it. Or we could have two sections: Qualifications and Preferred Background (maybe Skills). But Preferred Background is like "Preferred Background". Could treat as Skills? But better to have Qualifications and Preferred Background separate? The instruction says include a section ONLY when posting has real specific content. It has both Who Can Apply and Preferred Background. So we could have two sections: Qualifications (Who Can Apply) and Preferred Background (maybe as Skills). However the allowed headings list includes Skills. So we could use Skills for Preferred Background. But the instruction says "Use

    for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." So we can use Skills heading for Preferred Background. That seems appropriate. Thus sections: - About the role (intro paragraph) - Responsibilities (What You’ll Do) - Requirements (Requirements) - Qualifications (Who Can Apply) - Skills (Preferred Background) We must not include Pay, Schedule, Benefits as they are not present. Now we need to output HTML fragment only, no /, no markdown fences. We'll produce:

    About the role

    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.

    Responsibilities

    • 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

    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

    Qualifications

    • AI Engineers
    • Software Engineers
    • Senior Software Engineers
    • Backend Engineers
    • Systems Engineers
    • Platform Engineers
    • Infrastructure Engineers
    • Full-Stack Engineers
    • Developer Productivity Engineers
    • 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
    • Distributed