Senior Software Engineer – Application Reliability, Kubernetes, GCP, SQL

Cisco

. Own the reliability of AI-powered applications and features from the user's perspective .

Posted 9/24/2026full-timeUnited StatesSenior💰 $167,700 - $245,200 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining AI-powered applications with a strong focus on reliability and observability. Proficient in Python development, BigQuery SQL, and implementing SLI/SLO frameworks to enhance application performance and user experience.

Highest-signal resume keywords

Python DevelopmentBigQuery SQL ExpertiseGCP ExperienceApplication-Level SLI/SLO FrameworksAgent-Based Systems

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Hard Skills

Application ObservabilityAnomaly DetectionRoot Cause AnalysisFeature Flag ManagementAutomated RollbackComplex SQL QueriesSchema DesignDistributed TracingAgent Evaluation HarnessesOperational Analytics

Soft Skills

CollaborationLeadershipProblem Solving

Tools & Technologies

LookerBigQueryBigTableGKECloud LoggingCloud TraceCloud MonitoringLangGraph

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Engineering

Industry Keywords

AI-Powered ApplicationsObservabilityProduction OperationsAIOpsEvent-Driven Systems

Tech Stack

Tools & technologies

BigQueryCloudGoogle Cloud PlatformKubernetesPythonSQL

About the role

Key responsibilities & impact

Own the reliability of AI-powered applications and features from the user's perspective
Define, implement, and enforce feature-level SLIs, SLOs, and error budgets for APIs, RAG systems, AI agents, and user-facing applications
Build and maintain application observability systems using Looker dashboards on BigQuery and BigTable
Design and build LangGraph-based agents for automated issue identification and remediation
Implement anomaly detection, root cause diagnosis, auto-rollback, feature-flag kill switches, and self-healing workflows
Develop agent evaluation harnesses for benchmarking, multi-step workflow testing, non-deterministic outputs, and regression testing
Write complex BigQuery SQL for usage trend analysis, anomaly detection, and operational analytics
Design BigQuery table schemas optimized for observability and debugging
Analyze application usage trends and adoption metrics to identify reliability risks, capacity needs, and degraded user experiences
Partner with application development teams to embed deployment safety, structured logging, and distributed tracing practices
Lead application-level incident response, root cause analysis, and blameless postmortems
Build Python tooling and automation to reduce application-layer MTTD and MTTR
Apply emerging AI techniques to improve platform reliability and developer productivity
Collaborate with application developers, data engineers, infrastructure SREs, PMs, and leadership

Requirements

What you’ll need

7+ years of experience in software engineering with significant focus on reliability, observability, or production operations
Bachelor's or Master's Degree in Computer Science, Engineering, or a related technical discipline
Strong Python development skills
Experience building production tooling, automation, and agent-based systems
Production GCP experience deploying and managing applications on GKE (Kubernetes)
Deep SQL expertise with BigQuery, including complex queries, window functions, schema design, and cost optimization
Hands-on experience with BigTable or equivalent high-throughput operational data technology
Experience designing and operating application-level SLI/SLO frameworks, burn-rate alerting, and error budget policies
Strong application-layer debugging skills, including distributed tracing, profiling, structured log analysis, and dependency mapping
Experience building agent evaluation harnesses
Familiarity with A2A protocols, streaming architectures, and event-driven systems
Experience with feature flags, canary deployments, progressive rollouts, and automated rollback
Experience with GCP observability services such as Cloud Logging, Cloud Trace, and Cloud Monitoring
Exposure to AIOps concepts, including ML-driven anomaly detection, automated root cause analysis, and intelligent alerting
Experience driving SLO adoption, postmortem processes, and reliability reviews
Active engagement with the evolving AI ecosystem
Hands-on GenAI application development experience with LangGraph, agent engineering, prompt design, and agentic workflows
Experience building Looker dashboards and LookML models for operational observability

Benefits

Comp & perks

Medical, dental and vision insurance
401(k) plan with a Cisco matching contribution
Paid parental leave
Short- and long-term disability coverage
Basic life insurance
Cisco restricted stock unit grants may be available
10 paid holidays per full calendar year
1 floating holiday for non-exempt employees
Paid birthday day off
Paid year-end holiday shutdown
4 paid personal wellness days
16 days of paid vacation per full calendar year for non-exempt employees
Flexible vacation time off program for exempt employees
80 hours of sick time off provided on hire date and each January 1st thereafter
Up to 80 hours of unused sick time carried forward
Additional paid time away for critical or emergency family issues
Optional 10 paid volunteer days per full calendar year
Annual bonuses for non-sales roles, subject to Cisco’s policies
Incentive compensation for sales-plan employees, subject to applicable Cisco plan