Who we are Moveworks: the Agentic AI Assistant platform that empowers the entire workforce. Our platform enables employees to converse with all of their business systems through natural language to quickly find answers and automate tasks. Backed by Greylock and Sequoia.
About the role
We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Typically 8 or more years in security engineering, including 2 or more years focused on AI or LLM security
- Hands-on adversarial experience, such as red teaming, penetration testing or vulnerability research, applied to LLM systems
- Deep knowledge of LLM attacks and defenses (for example, the OWASP Top 10 for LLM Applications and MITRE ATLAS)
- Ability to identify risks, develop mitigation plans, and implement the fixes yourself
- Strong coding skills in Python or Go, and a record of shipping production code, not only findings
- Enough ML fundamentals to build evals and judge the efficacy of a classifier
More about this role
• Keep the map of ML usage and safeguards across our products current, and lead the security design of new ML features
• Break our safeguards: test the boundaries on jailbreaks, prompt injection, prompt leaks and toxicity, and turn findings into eval cases that run on every model, prompt and safeguard change
• Design and build mitigations with ML engineers that hold when detection misses
• Define the security metrics that show whether our safeguards work, and report on them
• Review changes that could weaken a safeguard
• Track AI attack research and turn new techniques into tests and mitigations
• Typically 8 or more years in security engineering, including 2 or more years focused on AI or LLM security
• Hands-on adversarial experience, such as red teaming, penetration testing or vulnerability research, applied to LLM systems
• Deep knowledge of LLM attacks and defenses (for example, the OWASP Top 10 for LLM Applications and MITRE ATLAS)
• Ability to identify risks, develop mitigation plans, and implement the fixes yourself
• Strong coding skills in Python or Go, and a record of shipping production code, not only findings
• Enough ML fundamentals to build evals and judge the...
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