Senior Security Engineer - Vulnerability Research
New
T
TaniumCybersecurity software
Remote, USFull-TimeSenior
SalaryThe annual base salary range for this full-time position is $191,000 to $293,000.
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Job Details
- Experience
- 5+ years industry experience, 7+ preferred
- Required Skills
- PythonC++Go
Requirements
- Have a Bachelor's degree in Computer Science or another relevant degree, or equivalent experience.
- Have 5+ years of industry experience; 7+ years is preferred.
- Demonstrate a strong understanding of web and native application security.
- Have hands-on vulnerability research experience through source code review, manual application penetration testing, or fuzzing.
- Be able to assess vulnerability severity, exploitability, and business impact.
- Be able to read and write code in at least one of Go, C++, TypeScript/JavaScript, or Python.
- Have experience with the process of developing, building, and shipping secure code.
- Preferred: experience applying frontier models to vulnerability research and evaluating where AI improves outcomes or creates noise.
- Preferred: experience with reachability or exploitability analysis at scale.
- Preferred: experience with native code security (C/C++) in privileged or agent-based software.
- Preferred: experience with AWS or Azure.
- Preferred: published vulnerability research, credited CVEs, bounty findings, open-source security tooling, or conference talks.
- Preferred: understanding of applied cryptography, including encryption, hashing, and secure key management.
Responsibilities
- Select attack surfaces and bug classes for research, and build capabilities to discover new vulnerabilities.
- Triage newly discovered vulnerabilities and rank them by exploitability and actual impact.
- Provide engineering teams with patch guidance and working pull requests alongside vulnerability reports.
- Maintain a threat model of Tanium software and services and use it to guide research projects.
- Evaluate in-house and third-party frontier AI tooling and build agentic workflows around effective approaches.
- Build and maintain vulnerability research tooling, including AI skills, fuzzing harnesses, and static and dynamic analyzers.
- Reduce the time from detection to remediation by lowering false-positive rates and improving finding quality.
- Review source code and conduct targeted security assessments of high-risk components.
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