Lead Software Engineer - Site Reliability (SRE)

TL;DR

Lead Software Engineer - Site Reliability (SRE): Designing for resilience, automating recovery, and ensuring system stability and observability at scale with an accent on SLIs/SLOs and performance engineering. Focus on building automated monitoring pipelines, leading incident response, and implementing high-availability distributed systems.

Company

hirify.global builds uncomplicated service software that delivers exceptional employee and customer experiences through enterprise-grade CX and IT solutions.

What you will do

• Design and implement tools to improve system availability, latency, scalability, and overall health.
• Define SLIs/SLOs, manage error budgets, and drive performance engineering efforts.
• Build and maintain automated monitoring, alerting, and remediation pipelines.
• Lead incident response, perform root cause analysis, and drive blameless postmortems.
• Champion observability across services using logs, metrics, and traces.
• Contribute to infrastructure architecture, automation, and reliability roadmaps.

Requirements

• 7–12 years of experience in SRE, DevOps, or Production Engineering roles.
• Strong coding proficiency and in-depth Linux expertise for advanced troubleshooting.
• Practical experience with Docker and Kubernetes for application deployment and orchestration.
• Experience designing and maintaining Continuous Integration and Continuous Delivery (CI/CD) pipelines.
• Proficiency in Infrastructure as Code (IaC) tools and infrastructure automation.
• Deep knowledge of Disaster Recovery (DR) and High Availability (HA) strategies for distributed systems.

Nice to have

• Degree in Computer Science, Engineering, or a related field.
• Experience scaling services in production with high uptime targets (99.99%+).
• Proven track record of reducing incident frequency and improving MTTD/MTTR metrics.

Culture & Benefits

• Inclusive environment welcoming colleagues of all backgrounds, genders, and orientations.
• Commitment to equal opportunity and workplace diversity.
• People-first approach to AI and a culture of reducing complexity.