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About the Role
We are seeking a Member of Technical Staff, Vulnerability Management to own Inferact's vulnerability-management process for vLLM, ensuring the security and production-readiness of this critical AI infrastructure. You will investigate vulnerability reports, translate technical findings into actionable tasks for the core team, and collaborate with open-source maintainers, security firms, and researchers.
Responsibilities
- Develop a deep understanding of vLLM's architecture.
- Independently investigate vulnerability reports.
- Turn technical findings into clear, actionable work for the core team.
- Collaborate with vLLM maintainers, Red Hat counterparts, security firms, and researchers.
- Drive reports from initial triage through analysis and resolution.
- Coordinate fixes, security advisories, and releases.
- Identify practical security best practices to strengthen vLLM.
- Perform hands-on product security investigations.
- Exercise sound judgment and ownership of follow-through.
Requirements
- Hands-on product security experience, with a strong orientation toward infrastructure software and the security of complex software systems.
- Ability to read source code, debug unfamiliar systems, reproduce reported issues, and explain root cause and practical security impact.
- Strong systems reasoning, including understanding architecture, trust boundaries, deployment assumptions, and component interactions.
- Ability to learn vLLM's core architecture and independently manage vulnerability investigations.
- Sound prioritization and risk-assessment judgment.
- Clear documentation of evidence, affected behavior, remediation needs, and next steps.
- Strong written and verbal communication.
- Discretion with sensitive reports.
- Ability to work constructively with engineers, researchers, and external security collaborators.
- Experience with vulnerability management and security best practices for open-source infrastructure software.
- Experience coordinating vulnerability resolution across reporters, maintainers, security teams, and software releases.
- Familiarity with vLLM, inference engines, ML infrastructure, or similarly complex distributed software.
- Experience preparing security advisories, assessing affected versions, and working with CVE and coordinated-disclosure workflows.
- Experience translating security findings into practical architecture reviews, regression tests, secure development practices, or deployment guidance.
- Experience resolving vulnerabilities in an open-source infrastructure project and explaining technical contributions and coordination with maintainers.
- Experience building security tooling or automation.
- Experience turning recurring vulnerability patterns into maintainable fixes, tests, or documentation.
Skills
- Product security
- Infrastructure software security
- Complex software systems security
- Source code analysis
- Debugging
- Issue reproduction
- Root cause analysis
- Security impact assessment
- Systems reasoning
- Architecture understanding
- Trust boundary analysis
- Deployment assumption analysis
- Software component interaction analysis
- Vulnerability investigation
- Prioritization
- Risk assessment
- Documentation
- Written communication
- Verbal communication
- Vulnerability management
- Security best practices
- Open-source software
- Coordination
- Security advisories
- CVE workflows
- Coordinated disclosure
- Architecture reviews
- Regression testing
- Secure development practices
- Deployment guidance
- Security tooling
- Automation
Location
- San Francisco, California
- Remote in the US
Work Type
- Full-time
Experience Level
- Member of Technical Staff
Salary/Compensations
- $200,000 - $400,000 USD + equity
Benefits
- Visa sponsorship on a case-by-case basis
- Applicable benefits will be confirmed based on the final role location
About the Company
- Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster.
- Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware, a position that took years to build.