
The world works with ServiceNow.
Sr. Delivery Acceleration AI Engineer at ServiceNow
About the role
ROLE DESCRIPTION
As a Sr. Delivery Acceleration AI Engineer, you will design, develop, and optimize AI-powered autonomous implementation solutions that transform how Service Now Expert Services deliver customer implementations. Working within the Delivery Acceleration team, you’ll focus on building and refining AI agents that automate Service Now configuration, generate implementation artifacts, and accelerate time-to-deploy—turning what previously required weeks of manual effort into AI-driven delivery that produces production-ready outputs in hours.
This role requires deep expertise in prompt engineering, AI agent architecture, and an understanding of enterprise professional services delivery. You’ll work directly with autonomous implementation platforms built on large language models to create, test, and refine the AI-driven workflows that generate Service Now configurations, user stories, test scripts, and deployment packages for customer engagements.
Critically, you must understand the professional services go-to-market motion—how services are scoped, sold, estimated, and delivered—because the AI solutions you build must align with how consultants and sales teams position and execute customer engagements. Your work directly impacts delivery speed, quality, margin, and the customer experience.
Success requires balancing technical depth in AI/LLM systems with practical business acumen. You’ll operate in a fast-paced sprint cadence where AI capabilities evolve rapidly, requiring continuous experimentation, rigorous quality validation, and close collaboration with solution architects, product managers, and delivery consultants across AMS, EMEA, and APAC+JPN. You will partner closely with the platform administrator who owns operations, adoption, and governance for the AI-powered deal and delivery document generator, ensuring the AI agents and prompt assets you build are deployed, scaled, and governed effectively across the global delivery community.
WHAT YOU GET TO DO IN THIS ROLE: Design & Develop AI-Powered Implementation Agents
- Architect and build AI agent workflows that autonomously generate Service Now configurations, implementation plans, user stories, and test scripts from customer requirements
- Develop, test, and iterate sophisticated prompt chains and orchestration patterns that produce consistent, production-quality outputs across Service Now product workflows (ITSM, CSM, HRSD, SPM, etc.)
- Design multi-step agentic processes that handle complex implementation logic—scope validation, dependency mapping, configuration generation, and quality assurance—with minimal human intervention
- Build and maintain prompt libraries, templates, and reusable patterns that encode delivery best practices and Gold Implementation standards into AI agent behavior, partnering with the platform administrator on library structure, versioning, and publication to end users
- Partner with AI Architects and Solution Architects to ensure agent outputs align with Service Now platform strategy, product direction, and enterprise readiness standards
Lead Prompt Engineering & AI Quality Optimization
- Serve as a subject matter expert in prompt engineering techniques for large language models, including chain-of-thought reasoning, few-shot learning, structured output generation, and context window optimization
- Design and execute systematic prompt evaluation frameworks that measure output accuracy, consistency, completeness, and adherence to Service Now implementation standards
- Continuously optimize prompt performance through A/B testing, output analysis, and iterative refinement—treating prompts as production code with version control and quality gates, incorporating user feedback and quality-audit signals surfaced by the platform administrator and the champions network
- Develop guardrails and validation logic that ensure AI-generated configurations meet enterprise quality standards before being deployed to the Expert Services community
- Stay current on evolving platform capabilities and techniques, rapidly incorporating new approaches that improve agent accuracy and efficiency
Integrate AI Solutions with Professional Services GTM & Delivery
- Understand the full professional services lifecycle—from pre-sales scoping and estimation through delivery execution and go-live—and ensure AI agent capabilities map to real engagement workflows
- Design AI solutions that support accurate estimation by providing data on automated vs. manual effort, enabling services sales teams to right-size engagements
- Partner with delivery consultants to validate that AI-generated outputs are usable in real customer contexts, incorporating feedback into continuous improvement cycles
- Contribute to packaging AI-accelerated delivery into repeatable service offerings that can be positioned and sold by services and license sales teams
Build Platform Integrations & Delivery Automation
- Integrate AI agent outputs with the Service Now platform, customer engagement portals, and internal delivery systems to create seamless end-to-end automation
- Design APIs, data pipelines, and integration patterns that connect autonomous implementation tools with estimation systems, resource management platforms, and project tracking tools
- Build automated testing and validation workflows that verify AI-generated configurations against Service Now best practices and customer requirements before deployment
- Collaborate with the implementation platform team to embed AI capabilities into the customer and partner delivery experience
- Ensure all integrations meet enterprise security, data governance, and compliance standards
- Coordinate with the platform administrator on release management—staging validation, production rollout, and vendor escalation—so new AI capabilities reach users without disrupting platform stability
Drive Measurement & Continuous Improvement
- Establish quality metrics for AI agent outputs: accuracy rates, rework percentages, time savings, and customer acceptance rates, feeding these signals into the adoption and ROI metrics the platform administrator reports to A&M leadership
- Analyze agent performance data to identify improvement opportunities, failure patterns, and expansion use cases
- Contribute to the delivery acceleration roadmap by identifying where AI can fill capability gaps or replace manual processes
- Document engineering best practices, architectural patterns, and lessons learned to build organizational knowledge
- Participate in sprint ceremonies, code reviews, and cross-team collaboration in a two-week sprint cadence with monthly releases
To be successful in this role you have:
- 5+ years of experience in software engineering, AI/ML engineering, or technical consulting in enterprise software environments
- 2+ years of hands-on experience with large language models, prompt engineering, and AI agent development—not just using AI tools, but building production systems on top of them
- Demonstrated expertise in prompt engineering techniques: chain-of-thought reasoning, structured output generation, few-shot/zero-shot patterns, context window management, and systematic prompt evaluation
- Strong understanding of professional services delivery operations: how engagements are scoped, sold, estimated, staffed, and delivered
- Experience with API design, system integration, and building data pipelines that connect AI outputs to enterprise workflows
- Proficiency in Python, JavaScript/TypeScript, or similar languages used in AI agent development and automation
- Understanding of Service Now platform architecture, data models, and configuration patterns
- Excellent communication skills—ability to translate technical AI capabilities into business impact for non-technical stakeholders
- Experience working in agile, sprint-based environments with measurable delivery outcomes
Not required but nice to have:
- Experience building autonomous implementation or code generation systems that produce production-ready outputs
- Background in management consulting or professional services delivery operations
- Familiarity with Service Now implementation methodology and delivery best practices
- Experience with AI agent orchestration frameworks and multi-step workflow automation
- Knowledge of AI ethics, output validation, responsible AI practices, and enterprise governance requirements
- Service Now platform certifications (CSA, CIS, or similar)
- Experience with enterprise estimation tools, resource management platforms, or delivery automation systems
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
Service Now is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, 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 globaltalentss@servicenow.com 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), Service Now may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon Service Now obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.
It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — Service Now stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.
Required skills
Prompt engineering
AI agents
LLMs
Workflow automation
Quality validation
Cross-functional collaboration
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About ServiceNow

ServiceNow
PublicServiceNow, Inc. is an American software company that supplies a cloud computing platform for the creation and management of automated business workflows. The company was founded in Santa Clara, California, United States, in 2003 by Fred Luddy.
10,001+
Employees
Santa Clara
Headquarters
$150B
Valuation
Reviews
10 reviews
3.8
10 reviews
Work-life balance
2.8
Compensation
3.7
Culture
4.1
Career
3.4
Management
3.2
72%
Recommend to a friend
Pros
Supportive and collaborative team environment
Good training and development opportunities
Flexible work arrangements
Cons
Work-life balance challenges and heavy workload
Fast-paced and stressful work environment
Management and communication issues
Salary Ranges
59 data points
Junior/L3
Mid/L4
Senior/L5
Staff/L6
Junior/L3 · Data Informatics Analyst
1 reports
$87,176
total per year
Base
$67,059
Stock
-
Bonus
-
$87,176
$87,176
Interview experience
6 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer rate
17%
Interview process
1
Application Review
2
Recruiter Screen
3
Behavioral Interview
4
Technical Interview
5
Final Round
6
Offer
Common questions
Coding/Algorithm
Behavioral/STAR
Technical Knowledge
Past Experience
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