Site Reliability Engineer (AI)

Location: Remote; daily overlap with client business hours expected

Company

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

What you will do

• Design observability systems covering metrics, logging, tracing, alerting, SLOs, error budgets, and monitoring strategies.
• Own the 24/7 P0 on-call rotation with a 10-minute acknowledgment SLA, validate AI-generated incident reports, and coordinate escalations.
• Lead incident response, troubleshooting, root-cause analysis, postmortems, capacity planning, and performance optimization.
• Build self-healing automation, reduce operational toil, and establish reliability standards and SLA targets for backend services.
• Collaborate with development, platform, operations, security, and client teams; review infrastructure changes and integrate reliability into delivery.
• Create runbooks and architecture documentation, mentor and onboard SRE engineers, and advise leadership on reliability strategy.

Requirements

• 6+ years of hands-on experience in SRE, DevOps, or Platform Engineering at scale.
• Deep AWS expertise, including ALB, ECS/Fargate, RDS Aurora, Lambda, and IAM.
• Production Python backend engineering experience, including debugging and optimizing Python services in containers and Lambdas.
• Availability for on-call rotation and support during and after business hours, including 24/7 P0 coverage with a 10-minute acknowledgment SLA.
• Experience building or bootstrapping SRE programs from scratch, with incident response, on-call rotations, postmortems, and SLOs.
• Deep experience designing and implementing observability through metrics, logging, tracing, and alerting.
• Solid understanding of Kubernetes, Docker, deployment automation, infrastructure-as-code with Terraform, CloudFormation, Pulumi, or similar tools, and CI/CD pipelines.
• Ability to troubleshoot distributed systems and complex production failures, with scripting proficiency in Python, Bash, or Go and Linux/Unix administration fundamentals.
• Experience with Git, collaboration workflows, infrastructure automation patterns, clear stakeholder communication, and explaining reliability trade-offs.
• Ability to work independently, collaborate with client and Modus leaders, participate in discovery workshops and regular working sessions, document solutions, pair program, and coordinate across technical teams.
• Reliable high-speed internet.

Nice to have

• Experience designing or operating internal developer platforms.
• Familiarity with chaos engineering, resilience testing, or failure scenario planning.
• Cloud security and compliance experience, including audit readiness and security hardening.
• Experience with AI infrastructure, LLM serving, agentic system operations, or AI-generated incident report validation workflows.
• Experience mentoring junior engineers or leading technical design discussions.
• Cost optimization and cloud FinOps experience.
• Python performance tuning, backend optimization, and building SRE programs in high-growth or fast-scaling environments.

Culture & Benefits

• Fully remote work in a global team.
• Collaborative environment with client-facing teamwork, pair programming, code reviews, architecture reviews, and knowledge sharing.
• Opportunity to solve challenging reliability, observability, and operational problems using modern cloud platforms, Kubernetes, infrastructure-as-code, and AI services.
• Direct impact on system uptime, performance, operational efficiency, and enterprise SRE practices.
• Continuous improvement through incident learning and support for teams operating AI applications reliably and safely at scale.