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ServiceNow AI Research is seeking a Staff Research Scientist to work on enterprise agentic AI research questions that most AI labs do not have access to. You will contribute to research initiatives exploring how agents accumulate and reuse tacit knowledge, learn and improve continuously, and maintain resilience, safety, and privacy in complex enterprise environments at scale.
The team focuses on the real obstacles to enterprise agentic AI deployment: safety mechanisms, threat detection, privacy guarantees, and responsible AI practices. Unlike much of the AI and NLP community that concentrates on core agent capabilities, this role emphasizes the dimensions that determine actual adoption in operational reality. You will have the freedom to publish and advance the state of the art, with the rare advantage of testing hypotheses against real deployments rather than benchmarks.
As a Staff-level researcher, you will provide scientific leadership to cross-disciplinary teams bringing together researchers and engineers. You will influence technical decisions beyond your own team, particularly with product and engineering teams. You will set research agendas, not merely execute them—choosing problems before the community turns to them and explaining your rationale.
The role is based in Montreal with flexible work arrangements. ServiceNow operates a distributed work model 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 or MS in computer science, machine learning, or related field, or equivalent research experience
- 2+ years of research experience post-graduation, with significant portion in industrial setting or 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 research agenda: you have chosen problems before the community turned to them and 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 understand what it takes for results to survive production deployment
- Advanced use of agentic tools in your own research practice and willingness to advance team practices in this area
- Demonstrated ability to influence technical decisions beyond your own team, particularly with product and engineering teams
- Excellent communication skills, including ability to explain complex technical work to non-specialist audiences and executives
**Nice to have:**
- Expertise in agent memory and tacit knowledge, continual learning, safety and alignment, security and threat detection, privacy, or agent evaluation
- Experience with AI systems operating in real enterprise environments with compliance, governance, and scale constraints
- 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
- French language proficiency or interest in learning it in a bilingual Montreal work environment
