Director of Engineering (AI Control Tower)

Join ServiceNow as the Director of Engineering for the AI Control Tower, the central hub for governing AI models, agents, and datasets across the enterprise. You will lead one or more product areas within the AICT platform, driving product delivery, adoption, and AI-native engineering practices. You will also build and retain a high-performing engineering team and collaborate with cross-functional teams to deliver coherent experiences. This role requires a deep technical foundation in cloud-native SaaS, experience in driving adoption of early-stage products, and a strong understanding of database schema design and modern data platforms.

- Own the engineering roadmap for AI Control Tower product areas, translating product requirements into technical plans and managing delivery across a focused engineering team. - Drive the full arc from early release to meaningful customer adoption, learning fast, iterating based on real customer feedback, and building feedback loops that compound adoption over time. - Recruit, develop, and retain a high-performing engineering team, providing clear feedback, creating stretch opportunities, and building a team culture that encourages excellence.

- This isn't a role for someone who has managed mature systems. It's for someone who has built something from scratch — in a small, fast company where there was no playbook — and who is now ready to do it at the scale and ambition of ServiceNow - You are AI-native. You don't just understand AI conceptually — you use it daily, you build with it, and you bring that instinct into how your team designs and ships - Deep technical foundation in cloud-native SaaS, including multi-tenant architectures, large-scale API design (REST/gRPC), Kubernetes orchestration, multi-cloud platforms (AWS, Azure, GCP), Infrastructure as Code (Terraform, CloudFormation, Helm) - Demonstrable startup experience at a company with fewer than 100 employees, where you were hands-on building and shipping a product — not just working at a startup, but building one - Proven experience driving adoption of a 1.0 or early-stage product: you have the scars from a launch that didn't go perfectly and the wins from figuring out how to turn it around - 10+ years in software engineering with 4+ years leading engineering teams (as a manager of managers or strong senior manager) - Strong understanding of 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, database schema design, data modeling, and event-driven architectures - Track record of building and retaining engineering teams, including in competitive talent markets - Ability to operate at both the architectural level and the pull request level when it matters - Experience building governance, observability, or compliance products — you understand why enterprises care about auditability and have designed for it - Familiarity with agentic frameworks and the operational realities of running agents in production (tool reliability, context management, failure modes) - Background in enterprise security, IAM, or data governance - Familiarity with MCP, OpenAPI, or other AI interoperability standards - MS or PhD in Computer Science, AI, or a related technical field