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ServiceNow

Builds software that automates business workflows

Senior Staff Software Engineer - Agentic AI

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeSanta Clara, CA, USA

About the Job

Requirements

  • Have 14 or more years of software development experience with a Bachelor's degree, 8 or more years with a Master's degree, 5 or more years with a PhD, or equivalent work experience.
  • Have hands-on experience with cloud-native and AI-native systems or equivalent senior-level roles.
  • Have hands-on experience with LLM and AI systems at scale, including prompt engineering, agent design, retrieval systems, and production AI/ML services.
  • Have 5 or more years of hands-on experience building and scaling systems with third-party AI/ML services and platform APIs across multiple cloud providers.
  • Have 3 or more years of experience designing and building applications on platform-as-a-service or SaaS platforms; deep ServiceNow platform expertise at scale is preferred.
  • Have expert-level proficiency in Python, Java, and JavaScript/GlideScript, and deep expertise in ServiceNow scripting, APIs, and platform architecture.
  • Demonstrate expertise in distributed systems design, microservices architecture, and large-scale systems.
  • Have a proven track record designing high-performance, mission-critical data pipelines, embedding systems, and vector databases.
  • Have expert knowledge of LLM orchestration frameworks, RAG architectures, retrieval optimization, and vector database technologies.
  • Have deep expertise with cloud computing (AWS, GCP, or Azure), managed AI services, and infrastructure-as-code.
  • Have a strong background in Kubernetes, containerization, and cloud-native deployment patterns.
  • Have expertise building evaluation frameworks, metrics systems, and production monitoring for AI/ML systems.
  • Have experience with secure coding practices, responsible AI, and compliance requirements.
  • Have experience leading customer-critical initiatives or providing technical leadership on strategic accounts.

Responsibilities

  • Define technical vision and strategy for AI-native and cloud-native systems; establish multi-year technology roadmaps and architectural patterns.
  • 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, and best practices; assess new services and tools for organizational fit.
  • Establish and evolve technical standards, architectural principles, and engineering excellence standards across the organization.
  • Own the technical roadmap for critical business initiatives involving AI; evaluate feasibility and set realistic timelines.
  • Champion investment in foundational improvements, including refactoring, testing infrastructure, monitoring, and security, with organization-wide impact.
  • Influence platform-level decisions involving cost, latency, reliability, and model quality; balance business objectives with technical constraints.
  • Stay current with AI/ML research and industry trends and translate research into practical business applications.
  • Mentor and develop senior engineers and engineering leaders; support their growth into leadership and architectural roles.
  • Lead technical hiring, assess senior-level candidates, and contribute to building the engineering team.
  • Establish and enforce an engineering culture focused on technical excellence, learning, ownership, and collaboration.
  • Lead by example in code quality, testing discipline, security practices, and responsible AI principles.
  • Support manager and team leadership development by providing technical guidance to engineering managers and team leads.
  • Conduct architectural and design reviews and provide feedback that shapes technical decisions across the organization.
  • Foster 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 involving multiple teams, cloud infrastructure, and sophisticated AI/ML components.
  • Lead the design of evaluation frameworks, observability systems, and production monitoring for AI-driven features at scale.
  • Establish security architecture and responsible AI guardrails that scale across the platform.
  • Design high-performance data platforms, embedding systems, and retrieval pipelines for organization-wide needs.
  • Evaluate and guide adoption of new cloud services, managed AI services, and technologies.
  • Drive architectural decisions balancing performance, cost, scalability, reliability, developer experience, and business value.
  • Conduct research and prototyping on novel technical approaches and lead exploration of emerging AI/ML techniques.
  • Lead root-cause analysis and architectural reviews for critical incidents and drive improvements to prevent recurrence.
  • Communicate technical vision and strategy to executives, product leadership, and engineering teams and influence organizational priorities.
  • 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 credibility and trust.
  • Lead or contribute to technical due diligence for acquisitions, partnerships, and strategic technology evaluations.
  • Translate complex AI/ML concepts, trade-offs, and limitations for technical and executive audiences.
  • Advocate for technical health, engineering culture, and long-term sustainability over short-term pressures.
  • Participate in industry forums, conferences, and communities to enhance the organization's external reputation.
  • Lead technical interviews and design discussions and mentor interviewing skills across the engineering organization.
  • Develop innovative solutions to complex technical challenges, particularly AI/ML integration and distributed systems.
  • Prototype and validate new approaches and share learnings and best practices across the organization.
  • Contribute to critical code paths and architectures and model best practices in code quality, testing, and maintainability.
  • Build evaluation frameworks, monitoring systems, and testing infrastructure that scale across the organization.
  • Implement security best practices, responsible AI guardrails, and compliance mechanisms that serve as organizational templates.
  • Work with cloud services, managed AI services, Kubernetes, and infrastructure-as-code at an architectural level.
  • Troubleshoot and resolve 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 best practices and architectural standards for ServiceNow development across the organization.
  • Lead technical decisions on ServiceNow platform capabilities versus custom development trade-offs.
  • Drive adoption of ServiceNow platform features and managed services; evaluate and recommend 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 the organizational approach to customer support and issue resolution 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 support customer selection and onboarding processes.

Desired Qualifications

  • Have deep expertise with the ServiceNow platform at scale.

About the Company

ServiceNow

Builds software that automates business workflows

ServiceNow builds cloud software that helps large organizations manage work across IT, customer service, human resources, and security. Its applications handle tasks such as resolving support tickets, onboarding employees, and responding to customer requests. Businesses configure forms, approval steps, and automation through visual tools on a common platform, connecting existing systems and using AI to assist workers or carry out tasks. The company sells subscriptions to its applications and platform, with professional services helping customers implement and use the software. Founded in 2004, ServiceNow is headquartered in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
2004

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