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About This Role
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
We are seeking a Senior Director of UX Research who is passionate about leveraging AI technologies to create empowering and supportive experiences for people at work. You will be joining our 130\+ UX Research \& Insights (UXRI) Organization, in our rapidly scaling global Experience Team (EX) of over 1000 UX Professionals (Research, Design, Product Content, and Ops). Together we are working to create product experiences that people love.
This is the perfect role for a research executive who is passionate about changing the world of work, and the evolving needs of businesses digitizing the way they work, while supporting distributed, global teams. Businesses know that the employee experience is everything, and they must provide experiences that foster loyalty, collaboration, productivity, and support the employee through their career. As a leader you will have a massive impact on how businesses evolve to provide predictive, empowering and productivity\-boosting experiences for their employees and technology teams by putting AI to work. This leader must bring an AI\-native mindset — not just familiarity with AI concepts, but hands\-on fluency with modern AI practices such as evaluation frameworks, prompt engineering, and human\-in\-the\-loop workflows — and the executive gravitas to influence decision\-making at the highest levels of a complex, matrixed organization.
This role leads a UX research team that focuses on delivering AI\-driven product experiences that resonate with our customers. Our researchers, spanning diverse backgrounds such as HCI, Human Factors, Cognitive and Experimental Psychology, Product Market Research, and Behavioral Sciences, collaborate seamlessly with product management, engineering, and design teams across the product development lifecycle. At ServiceNow, UX research has an integral role, driving innovation and propelling our products forward. We value diversity and inclusion, recognizing that varied perspectives foster creativity and innovation. Success in this role hinges not only on empathy and understanding but also on a profound grasp of how cross\-functional collaboration drives delivery success and enhances end\-user outcomes. Our unwavering commitment to research and development fuels ServiceNow's success, shaping the future of AI\-driven enterprise solutions.
What you get to do in this role:
- Build and develop a high performing team of UX researchers and managers focused on UX for AI technologies, fostering a culture of innovation and user\-centricity.
- Bring a strong, well\-articulated point of view on the role of UX research in shaping AI\-driven products, and champion that perspective with senior leaders across Product, Engineering, and Design.
- Directly lead and manage managers and individual contributors.
- Drive strategic initiatives to shape research programs and strategies specifically tailored to AI\-driven product experiences, with a heavy focus on Generative AI.
- Model and embed AI\-native ways of working across the research organization — including modern evaluation methodologies, rapid prototyping with AI tools, and research\-informed guardrails for generative AI experiences.
- Navigate a large, matrixed organization to build alignment and influence product direction at the VP and C\-suite level, partnering cross\-functionally with Product, Engineering, Design, and Marketing leadership.
- Partner with stakeholders to define and prioritize research initiatives that align with business objectives and user needs.
- Mentor and develop a diverse team of researchers, ensuring high\-quality execution of all aspects of user research throughout the product lifecycle.
- Communicate research findings effectively, translating complex insights into actionable recommendations for key decision\-makers. Should be able to clearly communicate and rationalize strategy and product solutions to stakeholders based on tested and rationalized user\-centered insights and data.
- Stay abreast of industry trends and emerging technologies in AI (especially Generative AI), continuously evolving our research methodologies and approaches.
Qualifications Basic Qualifications:
- 15\+ years of research experience and 8\+ years of experience managing and developing strong research managers.
- Extensive experience in UX research, particularly focused on AI technologies and their application in digital workflows.
- Proven track record in leading research teams to deliver impactful insights that drive product experiences and innovation.
- AI\-native orientation with demonstrated fluency in current AI/ML practices — including evaluation frameworks, responsible AI, and generative AI product development — and experience translating that knowledge into research strategy.
- Solid organizational experience, managing multiple teams, and a passion for developing strong, diverse managers and team members.
- Strong executive presence and a clear point of view, capable of influencing product leaders and C\-level stakeholders in complex, matrixed organizations through human\-centered data and strategic storytelling.
Preferred Qualifications:
- Advanced degree or equivalent experience in Human\-Computer Interaction, Cognitive Psychology, Human Factors, or related fields.
- Expertise in user interface design, usability evaluation techniques, and statistical analysis within the context of AI\-driven products.
- A thought leader in AI and up to date with the latest trends in Generative AI. Needs to be a strong ambassador for the team internally and externally.
- Exceptional leadership skills, inspiring global teams to deliver innovative solutions that anticipate and meet user needs.
- Experience in creating and executing new and innovative research programs, strategies and approaches that help the team scale and have greater impact.
- Experience leading with a hybrid (in\-office and remote), distributed, global team, and finding creative ways to bring the team together to drive collaboration, relationship building and a strong culture.
- Proven success operating in large, matrixed enterprise organizations, with the ability to build coalitions, navigate ambiguity, and drive consensus across competing priorities.
- Deep alignment with ServiceNow's values — curiosity, collaboration, and a commitment to making work better for everyone — with a track record of embedding those values into team culture and decision\-making.
- Passion for building a collaborative, high\-trust culture that brings together varied perspectives and experiences to drive stronger outcomes.
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.
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.
From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.
Salary Context
This $254K-$445K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At ServiceNow, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($349K) sits 63% above the category median. Disclosed range: $254K to $445K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
ServiceNow AI Hiring
ServiceNow has 11 open AI roles right now. They're hiring across AI Engineering Manager, AI/ML Engineer, AI Agent Developer, AI Product Manager. Positions span Santa Clara, CA, US, San Francisco, CA, US, Kirkland, WA, US. Compensation range: $243K - $445K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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