Senior Software Engineer - Data Platform - Kubernetes - Distributed Systems
ServiceNow
- Location
- San Diego, CALIFORNIA, United States
- Employment
- Full Time
- Work model
- On-Site
- Level
- Senior
- Salary
- $128.9k – $219.1k/yr
- H-1B history
- 185 approvals (FY2023)
- Posted
- 3h ago
Skills
About this role
Senior Software Engineer - Data Platform - Kubernetes - Distributed Systems Full-time Employee Type: Regular Region: AMS - North America and Canada Work Persona: Flexible 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 Position Location: This is a Flexible (Hybrid) position. Flexible positions require 2 days per week in a ServiceNow office location. We have offices in several locations, including San Francisco, CA; Pleasanton, CA; Santa Clara, CA; San Diego, CA; and Kirkland, WA About the team: As a Senior Software Engineer with the Data Platform organization, you will be responsible for designing and implementing features and services within our cloud-native platform. What you get to do in this role: You will design, build, and operate features and services within the cloud-native platform, delivering well-defined work from implementation through to production with limited guidance. You will break features down into clear, executable tasks and deliver them iteratively, raising risks and trade-offs as you find them. You will collaborate with staff and senior engineers to align your work with the team’s designs and the platform’s standards. You will contribute to the reliability, scalability, and operability of what you build — writing tests and instrumentation, improving runbooks, and participating in on-call. You will spend nearly all of your time hands-on building — automation, tooling, and platform services that other teams depend on. You will support junior engineers through code review, pairing, and sharing what you learn. Qualifications To be successful in this role you have: Experience leveraging or critically thinking about how to integrate AI into engineering work — whether using AI-powered coding and operational tooling, automating workflows, or reasoning about how AI changes the way software and infrastructure are built. 5+ years of software development experience with a Bachelor's degree; OR 3+ years with a Master's degree; OR a PhD without experience; OR equivalent work experience. Hands-on experience building production software, with exposure to deploying and operating workloads on Kubernetes. Some hands-on experience with at least one major hyperscaler (AWS, Azure, GCP) and its core compute and networking primitives. A track record of reliably delivering features and improvements as a productive member of an engineering team. Working knowledge of containers, CI/CD pipelines, and Git-based development workflows. Good programming skills in Go (or another systems language with a willingness to work primarily in Go). It also helps if you have: Experience running workloads on managed Kubernetes (EKS/AKS/GKE). Familiarity with GitOps-based delivery and infrastructure-as-code tools such as Terraform. Exposure to observability tooling — metrics, logging, and dashboards. Familiarity with networking and security fundamentals — DNS, TLS, and IAM. Experience participating in an on-call rotation. For positions in this location, we offer a base pay of $128,900 - $219,100 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as