Senior Staff Platform Engineer (Kubernetes, Go/Python)

Worldwide | Oct. 28, 2026

Report as Closed

Company: ServiceNow

Country: Worldwide

Type: Remote

Employment: Full Time

Description:

Company Description

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

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.

  • 14+ 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 replicat

  Apply here:

  Web: Apply here

  ☆ Save job

  Emails: