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Salary: USD 221,200 - 387,100 / annual
ServiceNow is seeking a Director of Engineering to lead the AI Control Tower, the company's central hub for governing AI models, agents, and datasets across the enterprise. This is a foundational role building infrastructure for agentic AI at scale—not managing a mature system, but shipping a 1.0 product and driving it from early adoption to durable enterprise use.
Reporting to the VP of Engineering, AICT, you will own one or more product areas within the platform, with scope expanding as the product and team grow. You are AI-native: you use AI daily, build with it, and embed that instinct into how your team designs and ships.
Key responsibilities include:
**Product Delivery & Roadmap Execution**: Own the engineering roadmap for your AICT product areas, translating product requirements into technical plans, managing delivery across a focused team, and maintaining velocity in a fast-moving market.
**1.0 to Adoption**: Drive the full arc from early release to meaningful customer adoption. You understand that shipping a 1.0 is half the job; the other half is learning fast, iterating based on real customer behavior, and building feedback loops that compound adoption.
**AI-Native Engineering**: Set the standard for how your team uses AI in its own development practice—from AI-assisted code review and testing to designing platform features that treat AI agents as first-class users. Lead by example.
**Team Building**: Recruit, develop, and retain high-performing engineers. You are a strong technical voice who grows engineers, gives clear feedback, creates stretch opportunities, and builds a culture where people want to stay and do their best work.
**Cross-Functional Execution**: Work closely with Product Management, Design, and partner engineering teams to align dependencies and ship coherent experiences. Represent engineering in planning and review forums with senior leadership.
**Requirements:**
- 10+ years in software engineering with 4+ years leading engineering teams (as a manager of managers or strong senior manager)
- Demonstrable startup experience at a company with fewer than 100 employees, where you were hands-on building and shipping a product
- 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 turning it around
- Deep technical foundation in cloud-native SaaS: multi-tenant architectures, large-scale API design (REST/gRPC), Kubernetes orchestration, multi-cloud platforms (AWS, Azure, GCP), Infrastructure as Code (Terraform, CloudFormation, Helm)
- 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
- AI-Native Engineering: Lead the adoption of AI across the entire engineering lifecycle—from product strategy, PRDs, UX, architecture, implementation, code reviews, debugging, testing, security, CI/CD, deployment, observability, APM, operations, and documentation—to improve engineering productivity, software quality, reliability, customer experience, and delivery velocity
- Ability to operate at both the architectural level and the pull request level when it matters
- Track record of building and retaining engineering teams, including in competitive talent markets
**Preferred Qualifications:**
- Experience building governance, observability, or compliance products
- 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
