MCP Expert, Remote Remote (International)

Dover; India; Remote; INR 827,000 - 1,653,000; Part time

Job summary

Dover seeks an experienced contractor to help train next-generation AI systems, working remotely with flexible hours (~15 hrs/week). You'll apply software engineering knowledge to shape how models learn, reason, and perform by delivering high-quality inputs and robust code tasks.

You will design Reinforcement Learning Environments using MCP tools, fix bugs, implement features, refactor code, and optimize performance, while collaborating with distributed teams.

Qualifications

• Proficiency in Python3, Java, Rust, and TypeScript.
• Strong grasp of algorithms and data structures.
• Experience debugging complex software issues.
• Background in feature development and refactoring.
• Ability to optimize software for performance and scalability.
• Strong written and verbal communication; comfortable in remote teams.

Responsibilities

• Train next‑generation AI systems using real-world software inputs.
• Design Reinforcement Learning Environments with MCP tools.
• Fix bugs, implement features, refactor code, and optimize performance.
• Collaborate with distributed teams to ensure robust solutions.
• Develop reproducible environments and deterministic verification.

Skills

Python3

Java

Rust

Algorithms

C++ basics

TypeScript

Bug fixing

Feature implementation

Codebase refactoring

Performance optimization

Job description

Job Type:

Contractor (~15 hrs a week)

Location:

Remote

Schedule:

Flexible, you pick the hours and days (including weekends if desired)

Required Skills:

• Python3

• Java

• Rust

• Algorithms

• Basics c++

• Typescript

• Bug fixing

• Feature implementation

• Codebase refactoring

• Performance optimization

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

As an expert you will be creating Reinforcement Learning Environments which test an AI model’s ability to solve complex software engineering problems using Model Context Protocol (MCP) tools. Tasks may involve fixing bugs, implementing features, refactoring code, or optimizing performance while requiring agents to discover and reason over information from real MCP servers. You will design reproducible environments, deterministic verification, and golden reference solutions that accurately measure both MCP tool use and software engineering ability.

Required Skills and Qualifications:

• Proficiency in C++, Python, JAVA, GoLang, Typescript, or Rust.

• Deep understanding of algorithms, data structures, and performance tuning.

• Demonstrated experience in debugging complex software issues and delivering maintainable solutions.

• Strong background in feature development and codebase refactoring.

• Proven ability to optimize software for performance and scalability.

• Exceptional written and verbal communication skills, with a keen attention to detail.

• Track record of success in collaborative, cross-functional teams, ideally in remote settings.

Preferred Qualifications:

• Previous experience working on large-scale, distributed codebases.

• Familiarity with modern AI or machine learning systems is a plus, though not required.

• Background in participating in rigorous code reviews and contributing to the development of software best practices.

Process:

1. Complete AI Interview (approx. 30 minutes)

2. Technical Assessment (Tentative)

3. Hiring Manager review

Compensation Structure

Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.

Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.