Principal Machine Learning Engineer

In this role you will play a key role in defining and building the cloud-native infrastructure that powers ServiceNow's next generation of Agentic AI and conversational experiences. As a Principal Engineer, you will drive architecture and technical strategy across multiple engineering organizations while remaining deeply hands-on in solving complex platform and scalability challenges. • Lead the technical direction, architecture, and evolution of cloud-native platform services supporting Agentic AI initiatives. • Drive the design and implementation of scalable Kubernetes-based infrastructure that supports AI/ML and conversational workloads at enterprise scale. • Partner with engineering, infrastructure, product, and platform teams to modernize critical services and accelerate the transition to next-generation architectures. • Design and build highly available, secure, observable, and resilient distributed systems supporting mission-critical customer workloads. • Establish architectural standards, engineering best practices, and platform patterns that can be leveraged across multiple product teams. • Drive automation across infrastructure provisioning, deployment pipelines, service operations, monitoring, and incident response. • Evaluate and adopt emerging technologies in cloud-native infrastructure, Kubernetes, AI platforms, and distributed systems. • Mentoring senior engineers and providing technical leadership through influence across organizational boundaries. • Lead architecture reviews and provide guidance on scalability, reliability, performance, security, and operational excellence. • Partner closely with teams developing AI-powered experiences to ensure underlying infrastructure can support future growth and innovation. • Work with stakeholders across the organization to balance long-term platform investments with near-term product delivery goals. • Own technical initiatives from concept through production deployment while helping shape the future direction of ServiceNow's Agentic AI platform.    To be successful in this role, you have: • 15+ years of experience building large-scale distributed systems, cloud platforms, infrastructure services, or enterprise SaaS products. • Deep expertise in Java, Go, Python, or similar systems programming languages. • Proven experience designing, building, and operating highly scalable cloud-native architectures. • Expert knowledge of Kubernetes, containers, orchestration platforms, and modern cloud infrastructure. • Experience building platform services used across multiple engineering teams and products. • Strong understanding of distributed systems principles, including resiliency, fault tolerance, scalability, performance optimization, and observability. • Experience with AWS, Azure, or Google Cloud at large scale. • Expertise in CI/CD, infrastructure automation, GitOps, Terraform, Helm, ArgoCD, or comparable technologies. • Strong software engineering fundamentals including object-oriented design, system design, architecture patterns, and performance optimization. • Experience leading technical strategy and influencing architecture across multiple organizations without direct authority. • Demonstrated track record building new platform capabilities from concept through large-scale production adoption. • Strong communication skills with the ability to explain technical tradeoffs to engineering and executive leadership. Preferred Qualifications • Experience building infrastructure for AI/ML, generative AI, agentic systems, or conversational platforms. • Experience supporting GPU workloads, model serving, inference platforms, or AI runtime environments. • Experience with internal developer platforms, platform engineering, SRE, or cloud infrastructure orga