Expert

Director of Engineering - AI Control Tower

Santa Clara, United States · On-site

Company 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.

Job Description

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 that enterprises will depend on as agentic AI moves from experiment to production — and we need a Director of Engineering who has been in that position before: shipping a 1.0 product, fighting for its first users, and figuring out how to turn early traction into durable adoption.

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. Reporting to the VP of Engineering, AICT, you will lead one or more product areas within the AICT platform, with scope and ownership evolving as the product and team grow.

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.

What You Will Do

Product Delivery & Roadmap Execution Own the engineering roadmap for your AICT product areas — translating product requirements into technical plans, managing delivery across a focused engineering team, and maintaining the velocity needed to meet the demands of a fast-moving market. You have done this before and know the difference between motion and progress.

1.0 to Adoption Drive the full arc from early release to meaningful customer adoption. You understand that shipping a 1.0 is only half the job — the other half is learning fast, iterating based on what real customers do (not what they say), and building the feedback loops that compound adoption over time.

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 assume AI agents are first-class users. You lead by example: your team should see you using AI tools as fluently as you use a terminal.

Team Building Recruit, develop, and retain a high-performing engineering team. You are a strong technical voice who can also grow engineers — you give clear feedback, create stretch opportunities, and build the kind of team culture that makes 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.

Qualifications

Required

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 — 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
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)
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.
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

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

For positions in this location, we offer a base pay of $221,200 - $387,100, 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.

Additional Information

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance.

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.