Senior Director, AI Platform Engineering Management

Job description

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started. Join us to put AI to work for people. 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 scalin