SRE DevOps Engineer

Highbrow LLC; Overland Park, Atlanta, Frisco (KS, GA, TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Highbrow LLC is seeking an experienced SRE DevOps Engineer to join onsite teams in Overland Park, Kansas, Atlanta, GA, or Frisco, TX. You will manage Kubernetes clusters, automate responses, and drive reliability improvements.

You will lead incident response, design self-healing tooling, and mentor junior engineers, while collaborating with development teams on deployments and performance optimizations.

Qualifications

• Diagnose and resolve escalated incidents across multi-layer infrastructure.
• Proficient with Kubernetes, API proxies, and networking components.
• Automate troubleshooting and remediation to reduce toil.
• Deep understanding of monitoring, alerting, tracing and logging.
• Familiar with GitOps, CI/CD pipelines, and IaC tooling.
• Identify performance bottlenecks in SQL/NoSQL databases.
• Lead incident response and produce RCA documentation.
• Mentor L1 engineers and improve runbooks with automation.

Responsibilities

• 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.

Skills

Advanced Incident Troubleshooting &amp

Kubernetes & Container Orchestration

Automation & Scripting

Observability & Monitoring

CI/CD & GitOps

Database Troubleshooting

Incident Management & RCA

Mentorship & Runbook Improvement

Tools

Kubernetes

Go

Python

Bash

Ansible

Terraform

Jenkins

Job description

SRE DevOps Engineer

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

Requirements

Qualifications

• 4–9 years in SRE/DevOps/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/NoSQL).
• Proficient in automation and scripting (Python, Go,Ansible, Terraform,etc..)
• Strong observability/monitoring experience.
• Experience with CI/CD pipelines, GitOps, and infrastructure as code.
• Solid problem-solving and collaboration skills.

Job responsibilities

• 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.

Skills

Mandatory Skills (Must-Have)

• 1.Advanced Incident Troubleshooting & Resolution
  Expectation: Diagnose and resolve escalated incidents that L1 cannot handle,
  often across multiplelayers (infrastructure, application,network).
  Example: For an API outage,identify if the root cause is in Kubernetes pod networking,APIgateway 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/tolerations, and
  cluster autoscaler logs.
• 3.Automation & Scripting (Python, Go, Bash,Ansible, Terraform)
  Expectation: Write scripts and automation to reduce manual toil,enhance monitoring, and improveincident 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 GitOps workflows, CI/CD pipelines, and infrastructure provisioning.
  Example: Enhance Jenkins pipeline to add automated smoke tests before promoting Kubernetes
  deployments.
• 6. Database Troubleshooting (SQL & NoSQL)
  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.

Preferred Skills (Nice-to-Have)

• 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, ChatOps)
  Expectation: Integrate AI/ML-powered tools for anomaly detection and auto-remediation.
  Example: Implement a ChatOps 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.