Senior Staff AI Native Engineer - Kubernetes

Job Description

Job Description

What you get to do in this role:

• Lead the design and delivery of complex components and services within the cloud-native platform, owning them from design through production operation.

• Act as the technical lead for major features and initiatives within the team, translating ambiguous problems into clear, scalable, and executable designs.

• Partner with Principal and Distinguished Engineers to ensure alignment with broader platform architecture, engineering standards, and long-term technical strategy.

• Identify technical risks early and drive them to resolution, with a strong focus on reliability, scalability, operability, and engineering excellence.

• Maintain a strong hands-on presence across the development lifecycle, including designing, coding, and reviewing core systems such as Kubernetes operators, controllers, infrastructure automation, and platform services.

• Mentor mid-level and junior engineers while raising the engineering bar through code reviews, design reviews, technical guidance, and collaborative problem-solving.

Qualifications

To be successful in this role you have:

• • Experience leveraging or critically thinking about how to integrate AI into engineering and platform work—AI-powered tooling, automated operational workflows, agentic systems for fleet visibility and operations, or reasoning about AI’s impact on how infrastructure is built and run.

  • 12+ years of experience designing, building, and operating large-scale distributed systems and cloud-native platforms in production environments.

  • Demonstrated experience building and operating Kubernetes platform infrastructure at scale, with ownership of platform capabilities through deployment, upgrades, and production operations.

  • Hands-on developing Kubernetes Operators, Admission Controllers, or other platform extensions using Kubebuilder, Operator Framework, or similar technologies.

  • Experience operating both managed Kubernetes services (EKS, AKS, GKE) and self-managed Kubernetes environments.

  • Experience supporting cloud-native database platforms, large-scale data infrastructure, or stateful services on Kubernetes.

  • Strong software engineering expertise in Go, with hands-on experience developing Kubernetes Operators, Controllers, Custom Resource Definitions (CRDs), and platform automation capabilities.

  • Deep understanding of Kubernetes architecture, including orchestration, scheduling, security, storage, networking, and workload management.

  • Proven experience operating stateful and distributed workloads on Kubernetes, including databases, data services, or other mission-critical platform components.

  • Experience with public cloud platforms (AWS, Azure, or GCP), including compute, networking, security, and identity management services.

  • Strong background designing and building microservices, event-driven systems, and distributed application architectures.

  • Experience owning complex technical initiatives end-to-end, from architecture and design through implementation, deployment, and operational support.

  • Hands-on experience with containers, CI/CD, GitOps practices, and Infrastructure-as-Code using tools such as Terraform, Crossplane, or equivalent technologies.

  • Experience implementing observability and reliability best practices, including metrics, logging, tracing, monitoring, alerting, and service-level objectives.

  • Proven ability to drive technical strategy through architectural design reviews, technical proposals, and cross-functional collaboration.

  • Good to have:

  • Experience with container networking (CNI) and/or service mesh.

  • Experience with mTLS, workload identity, and secrets management at fleet scale.

  • Experience with observability—metrics, tracing, and SLOs.

  • Experience with Terraform, Crossplane, or similar declarative infrastructure tooling.

  • Experience designing or tuning distributed data or compute workloads on Kubernetes.

  Distributed Systems Expertise

  • Experience with large‑scale deployments of distributed systems.

  • Deep knowledge of replication, fault-tolerant, and HA strategies.

  • Experience working in DevOps environments to operationalize distributed platforms.

  • Strong expertise in designing and architecting platforms using:

  • Kubernetes (workload deployments, upgrades, monitoring and maintenance)

  • Apache Kafka (high‑scale clusters, topic/partition strategies, HA) is a plus

  • Redis (high‑scale clusters, HA) is a plus

  • Expertise in data formats such as Parquet, ORC, and Avro, along with compaction and governance strategies.

  • Ability to build scalable, fault‑tolerant ingestion and transformation workflows.

Additional Information

Work Personas

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Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity,  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 [email protected] 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), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. 

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