Principal Software Engineer (AI Control Tower)

Join ServiceNow as a Principal Software Engineer for the AI Control Tower, the central hub for governing AI models, agents, and datasets across the enterprise. You will lead the architectural design and implementation of core platform components, drive customer adoption, and set the standard for AI-native engineering practices. You will also mentor and provide technical guidance to your team, collaborate with cross-functional teams, and represent AICT in technical forums.

- Architect and implement core components of the AI Control Tower platform, translating complex product requirements into scalable technical plans. - Drive the full arc from early release to meaningful customer adoption, iterating based on real customer feedback and building feedback loops. - Lead cross-team technical initiatives and drive architecture decisions through clear reasoning and credibility, acting as a strong technical voice.

- Distributed systems & event-driven architecture expertise, with focus on scalability, reliability, fault tolerance, and operational observability - AI-native engineering practices: Proficiency across the full engineering lifecycle (architecture, implementation, debugging, security, CI/CD) using AI to drive delivery velocity and software quality - Startup mindset: Direct experience building and shipping products from zero—ideally in high-growth environments where you were hands-on with both code and architecture decisions - Hands-on mastery: Comfort operating at the highest architectural level while remaining deeply hands-on in code when it matters most - Deep expertise in database schema design, data modeling, and modern data platforms, including relational, graph, vector, columnar, OLAP, and streaming data architectures, with the ability to design scalable data models for AI and enterprise workloads - Technical influence without formal authority: Demonstrated ability to lead cross-team technical initiatives and drive architecture decisions through clear reasoning and credibility - 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) - 10+ years in software engineering, with a proven track record of shipping complex enterprise-grade SaaS products and managing their evolution through scale - Governance, observability, or compliance product experience — understanding auditability, enterprise risk frameworks, and regulatory requirements - Agent frameworks & production operations: Hands-on familiarity with agentic system challenges (tool reliability, context window management, failure modes, cost optimization) - Enterprise security, IAM, or data governance background - Familiarity with AI interoperability standards such as MCP, OpenAPI, or similar - Advanced Degree: MS or PhD in Computer Science, AI, or a related technical field