Senior Director, AI Platform Engineering Management

The Role
The AI Control Tower is ServiceNow’s central hub for governing every AI model, agent, and dataset across the enterprise. We’re building the infrastructure enterprises will depend on as agentic AI moves from experimentation into production.
We are looking for a Senior Director of Engineering who combines the instincts of a startup builder with the leadership experience required to scale products, teams, and organizations. You have built products from zero to one, navigated the uncertainty of early customer adoption, and then created the engineering organization, architecture, and operating model required to scale.
This is not simply a role for someone who has managed mature platforms. We are looking for a leader who has built something from scratch, ideally in an environment where there was no established playbook, and who can bring that entrepreneurial mindset to the scale and ambition of ServiceNow.
Reporting to the VP of Engineering, AICT, you will lead multiple engineering teams and product areas across the AI Control Tower platform. You will help define the technical strategy, organizational structure, engineering culture, and execution model as the platform and organization grow.
You are AI-native. You do not just understand AI conceptually. You use it, build with it, and understand how AI changes product architecture, engineering workflows, developer productivity, and the expectations customers have for enterprise software.
What You Will Do
Engineering Strategy & Organizational Leadership
Own engineering strategy across multiple AICT product areas, translating the broader product vision into technical priorities, organizational investments, and execution plans. Partner with VP-level Product and Engineering leadership to determine where to invest, what to simplify, and how the platform should evolve as customer adoption accelerates.
Zero-to-One and Scaling to Adoption
Lead the full journey from initial product creation through meaningful enterprise adoption and scale. Establish feedback loops between customers, Product, Engineering, and Design so teams can quickly identify what is working, change what is not, and turn early customer traction into durable adoption.
Technical Leadership & Architecture
Provide senior technical leadership across architecture, platform strategy, data architecture, APIs, reliability, security, and operational scale. Establish architectural principles that allow multiple teams to move quickly without creating long-term platform fragmentation or technical debt. Stay close enough to the technology to challenge assumptions, review critical architectural decisions, and engage deeply when the situation requires it.
AI-Native Engineering
Set the strategy and expectations for how AI is used across the engineering organization. Drive adoption of AI throughout product definition, architecture, implementation, code review, debugging, testing, security, CI/CD, observability, operations, and documentation. Create measurable improvements in engineering productivity, software quality, reliability, customer experience, and delivery velocity.
Organization Building & Talent Leadership
Build and scale a high-performing engineering organization, including hiring and developing senior engineering managers, architects, technical leaders, and engineers. Create strong leadership succession, raise the technical bar, and establish a culture of accountability, experimentation, customer obsession, and continuous learning.
Portfolio & Roadmap Execution
Own execution across multiple teams and interconnected initiatives. Create mechanisms for prioritization, dependency management, technical decision-making, and delivery while ensuring teams remain responsive to a rapidly evolving AI market.
Cross-Functional & Executive Leadership
Partner closely with Product Management, Design, Security, Data, Infrastructure, and other engineering organizations. Represent AICT engineering in executive planning, architecture, investment, and product reviews. Communicate complex technical and organizational decisions clearly to senior leaders and influence priorities across organizational boundaries.
Customer & Market Leadership
Engage with strategic customers and field teams to understand how enterprises are deploying and governing AI in production. Translate customer problems into platform capabilities and use direct customer feedback to shape technical and product strategy.
Required
15+ years of software engineering experience, including significant experience leading large, complex engineering organizations and managing managers and senior technical leaders
Proven experience operating at the Director or Senior Director level, or equivalent scope, with accountability across multiple engineering teams or product areas
Demonstrable startup or zero-to-one experience where you personally helped build, launch, and scale a new product or platform, ideally in an organization with fewer than 100 employees
Proven experience taking an early-stage or 1.0 product through customer adoption and into meaningful scale, including navigating product-market uncertainty and changing direction based on customer behavior
Deep technical foundation in cloud-native SaaS, including multi-tenant architectures, large-scale API design such as REST and gRPC, Kubernetes, distributed systems, and multi-cloud platforms including AWS, Azure, and GCP
Strong understanding of Infrastructure as Code and modern cloud operations, including technologies such as Terraform, CloudFormation, and Helm
Strong understanding of database architecture, schema design, data modeling, and modern data platforms, including relational, graph, vector, columnar, OLAP, streaming, and event-driven architectures
Experience designing scalable data architectures that support AI, analytics, governance, and enterprise workloads
Proven ability to define technical strategy and architecture across multiple teams while balancing speed, reliability, security, scalability, and long-term maintainability
Demonstrated experience applying AI across the engineering lifecycle, including product strategy, architecture, development, testing, security, deployment, observability, operations, and developer productivity
Ability to operate comfortably from executive strategy and organizational design to architecture and implementation details when required
Track record of recruiting, developing, and retaining exceptional engineering leaders and technical talent
Strong executive communication skills with the ability to influence engineering, product, and business leaders across organizational boundaries
Preferred
Experience building governance, observability, compliance, or enterprise platform products where auditability, security, and explainability are core product requirements
Experience building or operating AI platforms, agentic systems, or AI infrastructure in production
Understanding of the operational realities of production AI agents, including tool reliability, context management, evaluation, observability, security, and failure modes
Background in enterprise security, IAM, data governance, or privacy
Familiarity with AI interoperability and integration standards such as MCP and OpenAPI
Experience engaging directly with large enterprise customers during the development and scaling of a new platform
MS or PhD in Computer Science, AI, or a related technical field
For positions in this location, we offer a base pay of $254,500 - $445,400, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

Skills
AWS, Azure, GCP, Kubernetes, CI/CD, Terraform, Data Modeling, Product Management, Documentation

Employment type
Full-time

Work arrangement
No