Principal Software Engineer

Company Description

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

About the Team

The Context Engine is ServiceNow’s platform for connecting enterprise data, knowledge graphs, and AI workloads into a single, governed context layer. We’re building the data infrastructure that AI agents and applications will depend on as enterprises move from pilots to production.

Types of problems you’ll get to work on

You’ll own the technical architecture of core components across the data lake (Iceberg, Polaris, Trino) and the Context Engine, taking them from early release to real adoption with customers.

Your core focus areas:

• Platform architecture. Lead design and implementation of lakehouse table services and context graph ingestion. Translate product requirements into scalable, observable plans with clear failure-recovery patterns.
• LLMs and ontologies. Design how large language models and enterprise ontologies work together in the Context Engine: ontology-grounded retrieval and reasoning for LLMs, and LLM-assisted ontology construction, mapping, and evolution. Make both production-grade, observable, and governed.
• 1.0 to adoption. Drive the full arc from early release to meaningful adoption. Learn from how customers actually use the platform, not only what they say, and build feedback loops that improve adoption over time.
• AI-native engineering. Set the bar for using AI in engineering itself, from AI-assisted code review and test generation to platform features that treat AI agents as first-class users.
• Engineering leadership. Run deep architecture reviews, raise the technical bar across the team, and represent the platform in technical and leadership forums.
• **Cross-functional...

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