ServiceNow is looking to build practical, AI-powered utilities and light-weight agents that streamline analytics workflows and boost stakeholder productivity for their Sales organization.
Requirements
- Solid Python scripting skills (e.g., data model build using common libraries, API calls) and strong SQL
- Exposure to AI agents/LLM apps through coursework, internships, hackathons, or personal projects
- Familiarity with Snowflake or Snowflake (or similar BI/cloud data platforms).
- Understanding of APIs/JSON/YAML, data structures, and software fundamentals.
- Knowledge of semantic modeling (Snowflake, Power BI models, basic DAX) and techniques for LLM-friendly data restructuring.
- Basic cloud familiarity (Azure/AWS/GCP) and workflow tools (e.g., schedulers/orchestrators).
Responsibilities
- Build and maintain scripts: Write clean, well-documented Python and SQL to ingest, transform, and validate data for Snowflake and Power BI datasets.
- AI agent prototyping: Under mentorship, help design and prototype AI-powered tools that analyze data from multiple perspectives, uncover patterns, and deliver quicker, more actionable insights.
- LLM-ready data prep: Convert enterprise data into LLM-optimized formats (semantic model, schemas, prompt-friendly outputs), ensuring reliability, basic guardrails, and reproducibility.
- ETL + quality checks: Contribute to simple ETL pipelines, unit tests, data quality checks, and runbooks; assist in monitoring scheduled jobs and triaging issues.
- Partner closely with the Data Technology org to ensure all AI agent work aligns with our AI Agent Build Framework - following approved workflow so the AI agents stay on the right path from day one.
Other
- 1–3 years professional experience (internships, co-ops, capstones count) in data/analytics engineering, ML/AI applications, or related fields.
- Growth mindset, attention to detail, and ability to learn from feedback and iterate quickly.
- Comfort explaining technical topics to non-technical partners and writing concise user docs.
- Experience supporting Sales analytics or familiarity with sales concepts (pipeline, bookings, opportunities) and CRM tools.
- Ability to work in a flexible, remote, or required in-office environment.
