Cybersecurity Expert for AI Training
G
Gramian Consulting GroupIT Professional Services
Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, Vietnam, 4 hours overlap with PSTContractSenior
Salary not disclosed
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Job Details
- Experience
- 4+ years of experience in cybersecurity, application security, vulnerability research, or offensive security
- Required Skills
- DockerNode.jsPythonCybersecurityGoRustLinux
Requirements
- 4+ years of experience in cybersecurity, application security, vulnerability research, or offensive security
- Hands-on experience with vulnerability discovery, exploit development, secure code review, or patch validation
- Strong understanding of web security, authentication, sessions, OAuth, JWT, SSRF, injection attacks, and access control vulnerabilities
- Experience with cryptographic vulnerabilities, filesystem attacks, or privilege escalation scenarios
- Experience using security tools such as SAST, fuzzers, IAST, or similar security testing frameworks
- Strong coding skills in at least two of the following languages: Go, Python, Node.js, Rust
- Experience working with Docker and containerized environments
- Familiarity with Linux internals and system-level behavior
- Experience with bug bounty programs, CTFs, red teaming, or CVE research is a strong plus
Responsibilities
- Design vulnerable multi-component applications and security challenge environments across languages such as Go, Python, Node.js, or Rust
- Develop realistic exploit chains combining multiple vulnerability categories and attack vectors
- Build deterministic evaluation environments using Docker and automated validation tooling
- Create security-focused test cases and verification logic for vulnerability detection and remediation workflows
- Review and analyze AI-generated outputs to identify gaps in reasoning, security understanding, or exploit detection
- Develop adversarial scenarios involving misleading documentation, obfuscated code, edge cases, and hidden attack paths
- Model real-world vulnerability classes inspired by CVEs, bug bounty findings, and production security incidents
- Ensure evaluation tasks remain scalable, reproducible, and resistant to contamination from public datasets
- Collaborate with cross-functional teams working on AI evaluation, benchmarking, and automated testing systems
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