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ServiceNow AI Research is seeking a Principal Research Scientist to lead research initiatives on enterprise agentic AI. You will work on research questions that most AI labs do not have access to, with a rare vantage point: observing how agents actually behave inside complex enterprise environments at scale.
You will lead research initiatives focused on how agents accumulate and reuse tacit knowledge, learn and improve continuously, and on their resilience, safety, and data privacy. These are the real obstacles to enterprise agentic deployment today, surfacing in operational reality well before they appear in academic literature.
While much of the AI and NLP community concentrates on core agent capabilities, this 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.
You will influence technical decisions beyond your own team, particularly with product and engineering teams. Strong communication skills are essential, including the ability to explain complex technical work to non-specialist audiences and executives.
ServiceNow approaches distributed work with flexibility and trust. Work personas (flexible, remote, or required in office) are assigned based on the nature of work and assigned location.
REQUIREMENTS:
- PhD in computer science, machine learning, or a related field, or equivalent research experience
- Eight or more years of research experience post-PhD, with a significant portion 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 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
