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About This Role
Director, ServiceNow Business Process Architecture
Remote – Western US (Pacific or Mountain time zone preferred)
Why Us
NewRocket is a ServiceNow Elite Partner and a Claude Select partner, helping enterprises reimagine how work gets done with ServiceNow and AI. We work with public and private sector organizations, including some of the world's biggest brands, to simplify processes, remove complexity, and turn the promise of AI into measurable business outcomes. We are "Raising the Bar" in delivering technology's promise to create new kinds of experiences for our customers.
Our Core Values: Excellence, Creativity, Integrity, Teamwork and Empathy #ExCITE. At NewRocket, these values guide everything we do: they are the foundation of our culture and define how we Go Beyond for our clients.
The Role
We are hiring a Director, Business Process Architecture within our Service Delivery organization, reporting to the Area Vice President, US West Delivery. This is a player-coach role: you will deliver directly with clients, leading process discovery and redesign on strategic ServiceNow and Claude engagements, while also leading and growing a team of Business Process Architects, supporting pre-sales, and building our AI-enabled business process practice.
As organizations move from digitizing workflows to redesigning them around AI agents, the way processes are designed has to change. You will help our clients, and our own team, make that shift by combining deep ServiceNow platform experience with hands-on knowledge of Now Assist, AI agents, and large language models such as Claude.
This role is a great fit for an experienced ServiceNow professional with a track record of leading engagements, customers, and project teams, including those ready to step into a more formal people-management role.
We are #GoingBeyond! Come join our crew!
What You Will Be Doing
Client Delivery
- Lead executive and stakeholder workshops to capture current-state processes, desired outcomes, and success measures across ServiceNow workflows and AI solutions such as Claude
- Redesign processes for an AI-first world: identify where Now Assist, AI agents, and LLMs such as Claude can automate, augment, or remove work, and where human judgment must stay in the loop
- Define future-state process architecture, requirements, and roadmaps, and make recommendations that improve efficiency, effectiveness, and experience
- Partner with Solution and Technical Architects to translate process designs into implementation plans
- Use AI tools such as Claude in your own delivery work to speed up discovery, process mapping, documentation, and analysis
- Serve as a trusted advisor to client leaders; identify and mitigate risk and escalate appropriately
Team Leadership
- Hire, coach, and develop a growing team of Business Process Architects, including career progression, performance reviews, and mentoring
- Upskill the team on Now Assist, AI agents, and Claude so every Business Process Architect can confidently lead AI-driven process conversations
- Conduct peer reviews to ensure quality and consistent use of leading practices
- Manage team financials, including utilization, revenue, and margin targets
Pre-Sales and Practice Building
- Support sales with scoping, estimates, SOW development, and client presentations for process and AI-led engagements
- Build packaged offerings for AI process redesign and agentic readiness, such as AI opportunity assessments and process redesign accelerators
- Develop reusable methods, templates, and AI-enabled tools that make our delivery faster and more consistent
- Provide input to Delivery leadership on strategy, hiring, and process improvements, and collaborate across NewRocket on special initiatives
What You Bring Along
- 8+ years of ServiceNow experience, with broad platform knowledge across multiple workflows (e.g., ITSM, CSM, HRSD, SPM) rather than a single module
- Hands-on experience applying AI to business processes, including ServiceNow Now Assist and AI Agents, and LLMs such as Claude
- Ability to rethink processes around AI and agentic automation, not just digitize the current state
- Proven experience leading engagements, programs, or customer relationships end to end
- Demonstrated leadership, formal or informal (e.g., engagement lead, workstream lead, or acting manager); prior people management is a plus but not required
- Experience supporting pre-sales, including scoping, estimating, and presenting to prospective clients
- Excellent facilitation and presentation skills, with the presence to lead executive-level workshops
- Strong written and verbal communication skills with all levels of an organization, including executives
- Strong coaching and mentoring skills, with the ability to motivate a team
- Strong problem-solving skills and the ability to simplify complex situations
- Comfortable with ambiguity, change, and working in a matrixed consulting environment
Certifications & Knowledge
- ServiceNow Certified System Administrator (CSA) required
- One or more ServiceNow Certified Implementation Specialist (CIS) certifications preferred
- ServiceNow AI certifications (e.g., Now Assist micro-certifications) preferred
- Claude certifications (such as the CCAR-F or CCDV-F) preferred; if you don't hold them yet, you must be willing to earn them within your first 90 days
We Take Care of Our People
NewRocket is committed to a diverse and inclusive workplace. We value and celebrate diversity, believing that every employee matters and should be respected and heard. We are proud to be an equal opportunity workplace and affirmative action employer, committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin, or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, citizenship, military, or Veteran status. For individuals with disabilities who would like to request an accommodation, please contact [email protected].
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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At NewRocket, 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 $212,000 based on 11,866 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,250.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
NewRocket AI Hiring
NewRocket has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Vista, CA, US, New York, NY.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 roles, $210,000 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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