Job Title: Software Engineering

Job Type: Contractor (10-15 hours per week)

Location: Remote

Job Summary:

We are looking for experienced software engineers to help train and evaluate next-generation AI systems through real-world software engineering tasks. This role is best suited for developers who can reason through unfamiliar codebases, explain engineering decisions clearly, and solve practical backend, full-stack, systems, or infrastructure-related problems.

A Cybersecurity/SecOps background or exposure is highly preferred

As and expert you will be creating Reinforcement Learning Environments which test an AI model's ability to find and patch security vulnerabilities in code. Your task will be to create a reproducible RL env in which a known CVE is present/injected in the repository and must be fixed by the model.

Key Responsibilities:

1. Work on challenging software engineering tasks across backend, full-stack, infrastructure, and systems-related projects.
2. Review, debug, improve, and explain code across different technical environments.
3. Design or evaluate practical solutions involving APIs, databases, services, integrations, testing, and deployment workflows.
4. Identify tradeoffs around scalability, maintainability, performance, reliability, security, and developer experience.
5. Communicate technical reasoning clearly in writing, including why a solution works and what alternatives were considered.
6. Collaborate with the customer’s team on technical reviews, implementation decisions, and problem-solving exercises.
7. Adapt quickly to new codebases, frameworks, and technical requirements.

Required Skills and Qualifications:

1. 3+ years of hands-on software engineering experience.
2. Strong experience in at least one backend or full-stack engineering environment, such as Python, JavaScript/TypeScript, Node.js, Java, C++, Go or Rust
3. Experience building, maintaining, or reviewing production-level applications, APIs, services, databases, or integrations.
4. Strong understanding of software engineering fundamentals, including debugging, testing, code quality, architecture, and technical tradeoffs.
5. Ability to explain complex engineering decisions clearly and objectively.
6. Comfortable reading and reasoning through unfamiliar code or technical requirements

Preferred Qualifications:

1. Experience with cloud environments such as AWS, GCP, or Azure.
2. Experience with CI/CD pipelines, DevOps workflows, containers, monitoring, or production operations.