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Salary: USD 221,200 - 387,100 / annual
ServiceNow is building the AI Control Tower (AICT), a central governance hub for managing AI models, agents, and datasets across enterprises. As a Principal Software Engineer, you will drive the technical architecture for critical platform components that will become standard infrastructure for enterprise-scale AI operations.
You will report to the Director of Engineering, AICT, and own the full arc from 1.0 product launch through meaningful customer adoption. Your responsibilities include:
**Technical Architecture & Leadership**: Lead architectural design and implementation of core AICT platform components. Translate complex product requirements into scalable, observable technical plans with robust failure recovery patterns. Set the technical standard for governance infrastructure.
**1.0 to Adoption**: Drive the complete journey from early release to customer adoption. Learn rapidly from real customer usage patterns, iterate based on actual behavior, and build feedback loops that compound adoption over time.
**AI-Native Engineering**: Set the bar for how the team uses AI in engineering itself—from AI-assisted code review and automated testing to designing platform features that treat AI agents as first-class users. Lead by example in leveraging AI to improve delivery velocity and software quality.
**Mentorship & Technical Excellence**: Act as the strong technical voice raising the bar across the organization. Run deep-dive architecture reviews, provide clear technical guidance, represent AICT in technical forums, and contribute to long-term platform strategy.
**Cross-Functional Execution**: Work closely with Product Management, Design, and partner engineering teams to align on dependencies and ship coherent experiences. Represent engineering in planning and review forums with senior leadership.
ServiceNow is the AI control tower for business reinvention, serving 85% of the Fortune 500. The company is building an AI-native culture where technology and talent drive meaningful work.
**Requirements:**
- 10+ years in software engineering with proven track record of shipping complex enterprise-grade SaaS products and managing their evolution through scale
- Deep technical foundation in cloud-native SaaS architecture: multi-tenant design, large-scale API design (REST/gRPC), Kubernetes orchestration, observability patterns, and multi-cloud platforms (AWS, Azure, GCP)
- Distributed systems & event-driven architecture expertise with focus on scalability, reliability, fault tolerance, and operational observability
- Deep expertise in database schema design, data modeling, and modern data platforms including relational, graph, vector, columnar, OLAP, and streaming data architectures; ability to design scalable data models for AI and enterprise workloads
- Startup mindset with direct experience building and shipping products from zero, ideally in high-growth environments where hands-on with both code and architecture decisions
- AI-native engineering practices: proficiency across full engineering lifecycle (architecture, implementation, debugging, security, CI/CD) using AI to drive delivery velocity and software quality
- Technical influence without formal authority: demonstrated ability to lead cross-team technical initiatives and drive architecture decisions through clear reasoning and credibility
- Hands-on mastery: comfort operating at highest architectural level while remaining deeply hands-on in code when it matters most
**Nice to Have:**
- Governance, observability, or compliance product experience
- Agent frameworks & production operations experience
- Enterprise security, IAM, or data governance background
- Familiarity with AI interoperability standards (MCP, OpenAPI, or similar)
- MS or PhD in Computer Science, AI, or related technical field
