• Design, build and ship safeguards in the agent harness for prompt injection, single and multi-turn jailbreaks, toxicity and sensitive topics, and sensitive data exposure
• Build evals that measure safeguard efficacy on both false and true positives, using datasets from customer reports, adversarial testing and production traffic
• Work closely with our Security team: turn their adversarial findings into eval cases and fixes, and build mitigations together that hold when detection misses
• Select, integrate and fine-tune detection models within a stack shared by our commercial and government environments
• Balance quality, latency and cost for controls that run in the request path
• Build configurable safeguard policies so customers can decide how sensitive topics are handled
• Monitor safeguard behavior in production and fix regressions
• Typically 8 or more years building production software, including 3 or more years of applied ML (training, evaluating and deploying models in production systems)
• Hands-on experience developing safeguards for LLMs, such as guardrail models, content classifiers, prompt injection or jailbreak detection, or safety evals
• Strong model evaluation fundamentals for agent trajectories and text classification, and attention to the quality of training and evaluation data
• Working knowledge of how LLM safeguards get bypassed, including indirect prompt injection through tools and documents, and multi-turn jailbreaks
• Excellent Python Experience
For positions in this location, we offer a base pay of $201,300 - $352,300, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs.
Compensation is based on the geographic location in which the role is located and is subject to change based on work location.
Work Personas
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.
Equal Opportunity Employer
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
Accommodations
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance.
Export Control Regulations
For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
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