Senior Staff Software Engineer - Agentic AI

ServiceNow•Santa Clara, CA

1d•$190,900 - $334,100

About The Position

ServiceNow is seeking a Senior Staff Engineer (IC5) to set technical vision and architecture across AI-native and cloud-native systems. This strategic technical leader will drive innovation, shape engineering culture, and influence platform direction, taking on the organization’s highest-impact and most complex problems. The role defines approaches to novel AI/ML challenges, establishes scalable best practices, and aligns technical strategy with business objectives. It combines deep technical expertise and systems thinking with organizational influence and the ability to mentor senior engineers, while serving as a trusted technical advisor to leadership and teams across the organization. The engineer will guide AI-native platform development, architecture, and software engineering practices, including evaluation frameworks, monitoring, security, deployment, data platforms, embedding systems, and retrieval pipelines. They will make architectural decisions across teams and cloud infrastructure, lead research and prototyping, and help resolve critical production incidents. The role also requires communicating technical strategy to executives, customers, product leaders, and engineering teams; influencing roadmaps; and contributing to strategic customer and partnership discussions. The position includes defining architecture and integration practices for AI-native ServiceNow applications, guiding the use of ServiceNow capabilities versus custom development, and partnering with ServiceNow product teams on advanced integrations. It also includes shaping customer support and escalation practices, engaging with strategic customers, and using customer feedback to inform product and platform strategy. Candidates must have substantial software development experience and hands-on experience with cloud-native and AI-native systems. The posting describes experience thresholds based on education: 14+ years with a bachelor’s degree, 8+ years with a master’s degree, 5+ years with a PhD, or equivalent work experience. The role requires expertise in AI/ML systems, distributed systems, cloud services, ServiceNow development, and production-scale architecture.

Requirements

14+ years of software development experience with a bachelor’s degree; or 8+ years with a master’s degree; or 5+ years with a PhD; or equivalent work experience.
Hands-on experience with cloud-native and AI-native systems, or equivalent senior-level roles.
Hands-on experience with LLM/AI systems at scale, including prompt engineering, agent design, retrieval systems, and production AI/ML services.
5+ years of hands-on experience building and scaling systems with third-party AI/ML services and platform APIs across multiple cloud providers.
Expert-level proficiency in Python, Java, and JavaScript/GlideScript.
Expertise in ServiceNow scripting, APIs, and platform architecture.
Demonstrated expertise in distributed systems design, microservices architecture, and large-scale systems.
Proven track record designing high-performance, mission-critical data pipelines, embedding systems, and vector databases.
Expert knowledge of LLM orchestration frameworks, RAG architectures, retrieval optimization, and vector database technologies.
Deep expertise in cloud computing (AWS/GCP/Azure), managed AI services, and infrastructure-as-code.
Strong background in Kubernetes, containerization, and cloud-native deployment patterns.
Expertise in building evaluation frameworks, metrics systems, and production monitoring for AI/ML systems.
Experience with and strong opinions about secure coding practices, responsible AI, and compliance requirements.
Experience leading customer-critical initiatives or providing technical leadership on strategic accounts.

Nice To Haves

Deep expertise with the ServiceNow platform at scale is preferred.

Responsibilities

Define technical vision, strategy, multi-year roadmaps, and architectural patterns for AI-native and cloud-native systems.
Lead development of core platforms and infrastructure that enable AI-native development at scale, including evaluation frameworks, monitoring, security, and deployment.
Drive adoption of emerging AI/ML technologies, frameworks, services, tools, and best practices; assess organizational fit.
Establish and evolve technical standards, architectural principles, and engineering excellence standards across the organization.
Own technical roadmaps for critical AI-related business initiatives, evaluate feasibility, and set realistic timelines.
Champion foundational improvements in areas such as refactoring, testing infrastructure, monitoring, and security.
Influence platform decisions involving cost, latency, reliability, and model quality while balancing business and technical considerations.
Track AI/ML research and industry trends and translate relevant advances into practical business applications.
Mentor and develop senior engineers and engineering leaders, supporting growth into leadership and architectural roles.
Lead senior-level technical hiring and contribute to building the engineering team.
Establish an engineering culture focused on technical excellence, learning, ownership, and collaboration.
Model code quality, testing discipline, security practices, and responsible AI principles.
Provide technical guidance to engineering managers and team leads and support their leadership development.
Conduct architectural and design reviews and provide feedback on technical decisions across the organization.
Promote knowledge sharing through documentation, technical talks, open-source contributions, and community engagement.
Create and refine career paths and professional development opportunities for engineering team members.
Design and architect large, complex systems spanning multiple teams, cloud infrastructure, and AI/ML components.
Lead design of evaluation frameworks, observability systems, and production monitoring for AI-driven features at scale.
Establish scalable security architecture and responsible AI guardrails.
Design high-performance data platforms, embedding systems, and retrieval pipelines for organization-wide needs.
Evaluate and guide adoption of cloud services, managed AI services, and other technologies.
Make architectural decisions balancing performance, cost, scalability, reliability, developer experience, and business value.
Research and prototype novel technical approaches and lead exploration of emerging AI/ML techniques.
Lead root cause analysis and architectural reviews for critical incidents and drive recurrence-prevention improvements.
Communicate technical vision and strategy to executives, product leadership, engineering teams, customers, and partners.
Partner with product, design, and domain specialists to define technical roadmaps aligned with business strategy.
Represent engineering in high-stakes customer and partnership discussions and build technical credibility and trust.
Lead or contribute to technical due diligence for acquisitions, partnerships, and strategic technology evaluations.
Explain AI/ML concepts, trade-offs, and limitations to audiences ranging from engineers to executive leadership.
Advocate for technical health, engineering culture, and long-term sustainability.
Participate in industry forums, conferences, and communities to support the organization’s external reputation.
Lead technical interviews and design discussions and mentor others in interviewing skills.
Develop innovative solutions to complex challenges, particularly involving AI/ML integration and distributed systems.
Prototype and validate approaches and share learnings and best practices across the organization.
Contribute to critical code paths and architectures, modeling code quality, testing, and maintainability.
Build scalable evaluation frameworks, monitoring systems, and testing infrastructure.
Implement security practices, responsible AI guardrails, and compliance mechanisms that can serve as organizational templates.
Work architecturally with cloud services, managed AI services, Kubernetes, and infrastructure-as-code.
Troubleshoot complex production issues and establish practices to prevent future incidents.
Contribute to open-source projects, research initiatives, or industry collaboration when aligned with business strategy.
Define platform architecture and integration patterns for AI-native ServiceNow applications.
Establish ServiceNow development best practices and architectural standards across the organization.
Lead technical decisions about ServiceNow platform capabilities versus custom development.
Drive adoption of ServiceNow platform features and managed services and evaluate platform upgrades.
Partner with ServiceNow product teams and technical account managers on advanced integrations and customizations.
Mentor senior engineers on ServiceNow platform architecture and advanced development patterns.
Ensure applications remain compatible with ServiceNow platform updates and evolution.
Shape organizational customer support and issue-resolution approaches and establish response and resolution standards.
Lead customer-critical incident response and complex troubleshooting and provide a technical escalation path.
Engage strategic customers on technical topics, roadmap alignment, and complex integration challenges.
Gather and synthesize customer feedback to inform product and platform strategy.
Establish programs and practices that improve customer experience and reduce support burden.
Work with customer success leadership to align technical capabilities with customer success metrics.
Lead technical due diligence and provide technical support in customer selection and onboarding processes.