SRE DevOps Engineer

Location:

Overland Park, KS / Atlanta, GA / Frisco, TX (Onsite)

• 4–9 years in SRE/Dev Ops/Systems Engineering as Senior or Principal Engineer
• Strong hands-on experience with Kubernetes, container orchestration, and API management.
• Working knowledge of WAFs,networking security, and database technologies (SQL/No
  
  SQL).
• Proficient in automation and scripting (Python, Go,Ansible, Terraform,etc..)
• Strong observability/monitoring experience.
• Experience with CI/CD pipelines, Git Ops, and infrastructure as code.
• Solid problem-solving and collaboration skills.

• Resolve escalated incidents across Kubernetes,API Proxy, WAF,DBs, and infra platforms.
• Design and improve runbooks, automating manual steps wherever possible.
• Lead and contribute to building self-healing systems and self-service tooling for users.
• Analyze incident trends, propose improvements in monitoring, capacity, and reliability.
• Collaborate with engineering teams on deployment, upgrades, and performance optimization.
• Conduct postmortems, document RCA, and ensure learning is captured.
• Mentor and coach L1 engineers.

• 1.Advanced Incident Troubleshooting & Resolution
  Expectation:
  Diagnose and resolve escalated incidents that L1 cannot handle,
  often across multiple layers (infrastructure, application,network).
  Example:
  For an API outage,identify if the root cause is in Kubernetes pod networking,API gateway misconfig,or backend DB latency — and apply fixes.
• 2. Kubernetes & Container Orchestration Expertise
  Expectation:
  Comfortable with deployments, scaling,networking, and debugging cluster-level
  issues.
  Example:
  Troubleshoot why pods are pending by checking node capacity, taints/tole rations, and
  cluster autoscaler logs.
• 3.Automation & Scripting (Python, Go, Bash,Ansible, Terraform)
  Expectation:
  Write scripts and automation to reduce manual toil,enhance monitoring, and improve incident resolution speed.
  Example:
  Develop a Python script to automatically collect pod and system logs when a service
  crashes.
• 4. Observability & Monitoring Tooling
  Expectation:
  Deep understanding of monitoring, alerting, tracing, and logging systems.
  Example:
  Build Prometheus alert rules to detect DB query spikes; configure Grafana dashboards for API latency.
• 5. CI/CD & Infrastructure as Code (IaC)
  Expectation:
  Familiarity with Git Ops workflows, CI/CD pipelines, and infrastructure provisioning.
  Example:
  Enhance Jenkins pipeline to add automated smoke tests before promoting Kubernetes
  deployments.
• 6. Database Troubleshooting (SQL & No
  
  SQL)
  Expectation:
  Identify performance bottlenecks, connection issues, and basic tuning opportunities.
  Example:
  Run queries to detect slow-running SQL statements causing latency in an application.
• 7. Incident Management & RCA
  Expectation:
  Act as incident commander for escalated issues, lead bridge calls, and produce Root
  Cause Analyses.
  Example:
  After a WAF misconfiguration causes downtime,lead the investigation, document the
  timeline, and propose preventive actions.
• 8. Mentorship & Runbook Improvement
  Expectation:
  Coach L1 engineers, refine runbooks, and introduce new automated workflows.
  Example:
  Update a runbook to add automated Kubernetes log collection instead of manual steps.

• 1. Cloud Platform Engineering (AWS,Azure, GCP)
  Expectation:
  Hands-on skills in provisioning, scaling, and securing cloud workloads.
  Example:
  Diagnose why an AWS ALB is misrouting traffic after a deployment.
• 2. Security & WAF Management
  Expectation:
  Understand WAF rules, common attacks (SQL injection, XSS), and how to apply fixes.
  Example:
  Investigate false positives in WAF logs and adjust rule sets with security teams.
• 3. Capacity & Performance Engineering
  Expectation:
  Anticipate scaling needs, tune resource utilization, and propose optimizations.
  Example:
  Identify that a Kubernetes deployment is CPU-throttled and adjust HPA (Horizontal Pod Autoscaler) configs.
• 4.Automation Platform Integration (AIOps, Chat Ops)
  Expectation:
  Integrate AI/ML-powered tools for anomaly detection and auto-remediation.
  Example:
  Implement a Chat Ops bot that runs predefined Kubernetes troubleshooting commands in Slack.
• 5. Cross-Platform Expertise (Hybrid Infra)
  Expectation:
  Experience supporting both on-prem and cloud environments seamlessly.
  Example:
  Compare latency patterns between on-prem DBs and cloud-hosted APIs to identify bottlenecks.