Site Reliability Engineer Engineer

Location: Remote only; daily overlap with client business hours is expected.

Company

hirify.global is a digital consulting partner that designs, builds, and modernizes digital products, platforms, and AI-powered experiences for client organizations.

What you will do

• Design observability systems covering metrics, logging, tracing, alerting, SLOs, and error budgets.
• Own 24/7 P0 on-call rotations with a 10-minute acknowledgment SLA and validate AI-generated incident reports.
• Lead incident response, troubleshooting, root-cause analysis, postmortems, and reliability improvements.
• Optimize capacity, latency, throughput, resource efficiency, and backend service performance.
• Build self-healing automation, reduce operational toil, and create runbooks and architecture documentation.
• Collaborate with developers, platform, operations, security, and client leadership while mentoring additional SRE engineers.

Requirements

• 6+ years of hands-on experience in SRE, DevOps, or platform engineering at scale.
• Deep AWS experience with ALB, ECS/Fargate, RDS Aurora, Lambda, and IAM.
• Production Python backend experience, including debugging and optimizing containerized and Lambda services.
• Experience building SRE programs, operating on-call rotations, conducting postmortems, and defining SLOs.
• Strong background in observability, distributed systems, Kubernetes, Docker, infrastructure as code, and CI/CD.
• Availability for client working-session overlap, reliable high-speed internet, and clear communication with technical stakeholders.

Nice to have

• Experience with internal developer platforms, chaos engineering, resilience testing, or failure planning.
• Cloud security, compliance, audit readiness, and FinOps experience.
• AI infrastructure, LLM serving, agentic system operations, or AI-generated incident report workflows.
• Experience mentoring engineers or leading technical design discussions.

Culture & Benefits

• Fully remote collaboration with client and Modus teams.
• Work with modern cloud platforms, Kubernetes, infrastructure as code, and observability tooling.
• Continuous improvement through incident learning and operational excellence.
• Direct impact on uptime, performance, reliability, and operational efficiency.
• Opportunities to shape enterprise SRE practices and support AI services reliably at scale.