Principal Research Engineer/Scientist at...

Company Description

It all started under the San Diego sun in California in 2004, when a visionary engineer, Fred Luddy, saw the potential to transform the way we work. Today, ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent, cloud-based platform seamlessly connects people, systems, and processes to enable organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us in our goal to make the world work better for everyone.

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

Job Description

As a Principal Researcher, you will work on research questions that most AI labs simply do not have access to. ServiceNow AI Research is chartered to build the future of enterprise agentic AI, from a rare vantage point: we see how agents actually behave, inside complex enterprise environments, at scale.

You will lead research initiatives on how agents accumulate and reuse tacit knowledge, learn and improve continuously, and on their resilience, their safety, and the privacy of the data they handle. These are the real obstacles to enterprise agentic deployment today, and they surface in operational reality well before they appear in the literature.

While much of the AI and NLP community concentrates on core agent capabilities, our team explores the dimensions that determine real adoption: safety mechanisms, threat detection, privacy guarantees, and responsible AI practices. You will have the freedom to publish and advance the state of the art, with the rare advantage of testing your hypotheses against real deployments rather than against benchmarks.

Qualifications

PhD in computer science, machine learning, or a related field, or equivalent research experience
Eight or more years of research experience post-PhD, a significant portion of it in an industrial setting or in direct contact with deployed systems
Established publication record at top-tier venues (NeurIPS, ICML, ICLR, ACL, EMNLP, or equivalents), with contributions recognized as influential in your field
Demonstrated track record of setting a research agenda, not only executing one: you have chosen problems before the community turned to them, and you can explain why
Experience providing scientific leadership to cross-disciplinary teams or projects bringing together researchers and engineers
Strong software development skills: you write, maintain, and optimize high-quality research code, and you know what it takes for a result to survive the move into production
Advanced use of agentic tools in your own research practice, and a willingness to advance the team's practices in this area
Demonstrated ability to influence technical decisions beyond your own team, particularly with product and engineering teams
Excellent communication skills, including the ability to explain complex technical work to non-specialist audiences and to executives

Nice to have

Expertise in one or more of the following areas: agent memory and tacit knowledge, continual learning, safety and alignment, security and threat detection, privacy, agent evaluation
Experience with AI systems operating in real enterprise environments, with the compliance, governance, and scale constraints that entails
Contributions to open source software, datasets, or evaluation benchmarks used by the community
Scientific service roles: program committees, editorial work, workshop organization
Academic collaborations or supervision of doctoral students
Fluency in French, or interest in learning it, in a bilingual Montreal work environment

Requirements

PhD in computer science, machine learning, or a related field, or equivalent research experience
Eight or more years of research experience post-PhD, a significant portion of it in an industrial setting or in direct contact with deployed systems
Established publication record at top-tier venues (NeurIPS, ICML, ICLR, ACL, EMNLP, or equivalents), with contributions recognized as influential in your field
Demonstrated track record of setting a research agenda, not only executing one: you have chosen problems before the community turned to them, and you can explain why
Experience providing scientific leadership to cross-disciplinary teams or projects bringing together researchers and engineers
Strong software development skills: you write, maintain, and optimize high-quality research code, and you know what it takes for a result to survive the move into production
Advanced use of agentic tools in your own research practice, and a willingness to advance the team's practices in this area
Demonstrated ability to influence technical decisions beyond your own team, particularly with product and engineering teams
Excellent communication skills, including the ability to explain complex technical work to non-specialist audiences and to executives

Nice to have

Expertise in one or more of the following areas: agent memory and tacit knowledge, continual learning, safety and alignment, security and threat detection, privacy, agent evaluation
Experience with AI systems operating in real enterprise environments, with the compliance, governance, and scale constraints that entails
Contributions to open source software, datasets, or evaluation benchmarks used by the community
Scientific service roles: program committees, editorial work, workshop organization
Academic collaborations or supervision of doctoral students
Fluency in French, or interest in learning it, in a bilingual Montreal work environment

Additional Information

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, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, 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.