Staff Software Engineer – SRE & AIOps

About the Role
ServiceNow is seeking a Staff Software Engineer – SRE & AIOps to drive infrastructure automation, operational resilience, and toil elimination across our hybrid cloud and data center operations. Embedded within the Site Reliability & Database Engineering organization, you will design and implement automation-first systems that reduce manual intervention, accelerate incident remediation, and enable our global engineering teams to operate reliably at scale.
This role combines strong hands-on technical expertise in Kubernetes, cloud platforms, and DevOps practices with technical leadership influence across infrastructure teams. You will architect SRE tooling, develop auto-remediation capabilities, and establish patterns that allow ServiceNow's cloud platform to maintain high reliability while minimizing operational toil across follow-the-sun global teams.
What you get to do in this role:
Design, deploy, and operate enterprise-scale Kubernetes clusters across hybrid and multi-cloud environments, establishing governance, scaling policies, and operational practices that support high-velocity application deployments at 99.99%+ availability targets.
Architect and implement closed-loop auto-remediation systems that detect, classify, and resolve transient infrastructure failures without human intervention, leveraging agentic AI and machine learning frameworks to predict failures, trigger preventive actions, and continuously reduce MTTR and on-call burden.
Design and evolve the SRE tooling stack, including monitoring platforms, incident management systems, log aggregation, and observability integrations, that support global follow-the-sun on-call operations and enable data-driven incident response.
Establish SLO frameworks, error budgets, and alerting policies that balance rapid incident response with alert fatigue management, while developing automated runbooks and playbooks that empower on-call engineers to resolve issues autonomously.
Design and maintain Infrastructure-as-Code frameworks and GitOps pipelines that enable reproducible, auditable infrastructure deployments across hybrid and multi-cloud environments with consistent security and compliance guardrails.
Architect hybrid cloud and data center operations, spanning on-premises infrastructure, public cloud environments, and edge computing, including workload migration strategies, disaster recovery patterns, and cost optimization practices across multi-region deployments.
Drive adoption of containerization, microservices, and DevOps patterns across engineering teams, establishing CI/CD best practices, service mesh architectures, and network security controls that enable rapid, safe release cycles.
Design on-call rotation schedules, escalation policies, and incident command systems that span across different time zones, ensuring 24/7 incident response while driving post-incident review processes that capture learning and drive systemic improvements.
Mentor and guide junior SRE engineers and infrastructure teams on reliability patterns, incident investigation techniques, automation best practices, and agentic AI applications for infrastructure operations.
Champion a culture of blameless incident analysis, data-driven decision-making, continuous improvement, and experimentation across engineering teams, establishing knowledge-sharing practices and technical documentation standards.
Reduce operational toil through systematic automation of repetitive tasks, from infrastructure provisioning to incident response to cost optimization, directly improving team capacity and job satisfaction across globally distributed operations.
To Be Successful in This Role You Have
Kubernetes Mastery: Strong hands-on expertise operating production Kubernetes clusters at scale, including cluster design, node management, pod orchestration, resource quotas, network policies, security controls, and troubleshooting complex runtime issues.
Incident Auto-Remediation Expertise: Proven experience designing and implementing closed-loop automated remediation systems, including anomaly detection, alert correlation, runbook automation, and self-healing mechanisms, that measurably reduce MTTR and on-call burden.
Cloud Platform Experience: Extensive hands-on experience with AWS (EKS, EC2, RDS, Lambda), Azure (AKS, VMs, CosmosDB), and GCP (GKE, Compute Engine, Cloud SQL), capable of architecting multi-region solutions.
DevOps & IaC Proficiency: Strong experience with Infrastructure-as-Code tools and GitOps platforms to drive reproducible, auditable infrastructure deployments.
SRE Tooling Fluency: Strong working knowledge of observability platforms, incident management systems, and log aggregation.
Distributed Systems Thinking: Solid understanding of distributed system challenges, eventual consistency, cascading failures, network partitions, and proven ability to design systems resilient to these conditions.
On-Call Operations: Experience operating in follow-the-sun, 24/7 on-call models; ability to design escalation policies, runbooks, and communication patterns that balance responsiveness with operator well-being.
Data Center & Hybrid Cloud Operations: Hands-on experience managing both on-premises infrastructure and public cloud environments, including hybrid networking, disaster recovery, and workload migration strategies.
AI/ML Integration: Demonstrated ability to apply machine learning and AI-driven insights to infrastructure operations, including anomaly detection, predictive alerting, and intelligent remediation.
Technical Leadership: Proven ability to drive technical decisions across teams and mentor engineers on reliability practices through credibility and technical depth.
Qualifications
Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.
8+ years in software engineering or infrastructure operations, with 5+ years in SRE, DevOps, or cloud platform engineering roles managing large-scale distributed systems with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience; or equivalent experience.
4+ years hands-on experience designing, deploying, and operating production Kubernetes clusters at scale.
Proficiency in Infrastructure-as-Code: Terraform, CloudFormation, or equivalent tools used to manage infrastructure at scale.
Public Cloud Expertise: Demonstrable experience across 2+ of the following: AWS, Azure, GCP, with solid knowledge of services relevant to SRE operations (compute, networking, storage, observability).
On-Call Operations: Experience operating or designing components of 24/7 follow-the-sun on-call models for distributed teams, including runbook development and incident response.
Incident Auto-Remediation: Proven ability to design and implement automated remediation systems that measurably reduce manual toil.
Linux & Systems Programming: Strong foundation in Linux system administration, performance troubleshooting, and scripting (Python, Go, Bash).
SRE Mindset: Demonstrated commitment to reliability through engineering, favoring durable automation over heroics, and data-driven decision-making.
Bachelor's degree in computer science, Computer Engineering, or related field (or equivalent professional experience).
Preferred:
Kubernetes certification (CKA, CKAD, or equivalent).
Experience with service mesh platforms or advanced networking in Kubernetes environments.
Background in migrating workloads from on-premises data centers to public cloud environments.
Experience with cost optimization practices in hybrid cloud environments (reserved instances, spot instances, resource right-sizing).
Track record of mentoring infrastructure engineering teams.
Why This Role?
This role offers the opportunity to eliminate operational toil at scale and build the automation-first infrastructure practices that define modern cloud operations. You will architect systems that allow ServiceNow's global teams to operate reliably with confidence in automated remediation systems actively preventing and resolving failures. Your work will directly shape how the organization scales reliability as it grows, establishing patterns that benefit teams across the platform. This is a role for an engineer who wants technical depth, team influence, and the satisfaction of watching systems recover from failure automatically.
For positions in this location, we offer a base pay of C$125,700 - $220,000, 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 qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

Employment type
Full-time

Work arrangement
Hybrid