Staff Research Engineer/Scientist

• Design & Architect Data Infrastructure — Design and oversee deployment of data architecture and pipelines to capture, manage, and store structured and unstructured data from internal and external sources; establish processes and data flows using cloud, local databases, and applicable storage forms • Build & Automate Data Transformation — Develop technical tools using ML and data-engineering techniques to cleanse, organize, and transform data; implement automated processes to maintain data structure integrity and quality standards on an ongoing basis • Define Agentic Evaluation Metrics & Ground Truth — Partner with product and AI teams to define evaluation metrics for agentic workflows (task completeness, tool use, workflow success); establish ground truth labeling standards and validation criteria; design evaluation datasets that reflect real-world agent execution • Build Agentic Evaluation Pipelines — Design and implement automated evaluation infrastructure that measures AI agent performance using Now LLM Service models and execution logs; create dashboards, reporting, versioning, and reproducibility of evaluation datasets and results • Establish Standards & Continuous Improvement — Create design standards and quality assurance processes for data systems; define quality gates and validation frameworks; analyze workflow performance and recommend optimizations to accommodate evolving CRM AI requirements • Lead Cross-Functional Collaboration — Collaborate with product, engineering, and data science teams; mentor junior engineers on data engineering and evaluation design; generalize evaluation patterns and metrics across Agentic AI products • 9+ years designing and building production data pipelines, data warehousing, ETL systems; strong expertise in SQL, Python, Javascript or equivalent, and distributed data processing • 3+ years working on ML systems, model validation infrastructure, automated testing, or AI-powered applications; hands-on experience with data quality, feature engineering, and model monitoring • Proven track record deploying, monitoring, and maintaining large-scale data systems in production; experience troubleshooting data quality issues, latency, and system reliability • Ability to design scalable, secure data architectures; experience with cloud platforms (GCP, AWS), APIs, event-driven systems, and data governance patterns • Familiarity with AI/ML evaluation frameworks, LLM-based systems, or agentic workflows; ability to instrument and evaluate complex AI systems; understanding of model performance tracking. • Comfortable driving technical conversations across multiple teams; takes end-to-end ownership; works autonomously; mentors peers on data engineering standards and best practices • Experience on ServiceNow platform is good to have. For positions in this location, we offer a base pay of $202,500 - $354,400 , 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 w