Staff Site Reliability Engineer (AI)

TL;DR

Staff Site Reliability Engineer (AI): Building and evolving the reliability foundation for an AWS-based platform that provisions, deploys, and operates AI agents supporting global payment infrastructure, with an accent on event-driven architecture, observability, and scalable infrastructure. Focus on defining SLOs and error budgets, replacing synchronous communication with durable asynchronous messaging, and solving complex distributed-systems and production-reliability challenges.

Location: Remote globally; the role is listed across Europe and can be performed from anywhere.

Company

hirify.global provides an AI-native global commerce operating system connecting enterprise merchants, banks, and wallets to payment, fraud prevention, KYC/KYB, and stablecoin infrastructure.

What you will do

• Define the platform-wide reliability strategy, including SLOs, SLIs, error budgets, incident practices, and engineering standards.
• Drive infrastructure architecture decisions and major platform evolutions as transaction volume and AI workloads scale.
• Design and own durable event-driven messaging for inter-service communication, including migration from synchronous patterns.
• Manage AWS infrastructure and infrastructure-as-code provisioning while operating Kubernetes and Docker workloads in production.
• Build observability through monitoring, alerting, dashboards, and distributed tracing, and lead incident response, postmortems, and root-cause analysis.
• Run chaos engineering and resilience experiments while mentoring engineers and raising reliability standards across teams.

Requirements

• 7+ years of experience in site reliability, infrastructure, or closely related engineering roles.
• Hands-on ownership of event-driven systems and messaging platforms such as Kafka, NATS, or RabbitMQ, including delivery semantics, consumer groups, dead letters, and backpressure.
• Deep AWS and networking knowledge, including EC2, VPC, IAM, S3, and RDS, plus Terraform or Pulumi experience.
• Production experience with Kubernetes, Docker, distributed-systems debugging, and automation using Go, Python, or a similar language.
• Experience defining and operating SLOs, SLIs, error budgets, observability platforms, chaos experiments, and resilience testing.
• Advanced written and spoken English proficiency required.

Nice to have

• Production AI or MLOps infrastructure experience, including model serving, LLM inference, GPU/resource management, and agent observability.
• Experience with multi-tenant container platforms, data pipelines, orchestration, or data warehouses.
• Payments-industry experience and incident-management tooling such as PagerDuty, Opsgenie, or incident.io.
• ECS, s6-overlay, or AI agent framework experience.
• Spanish proficiency.

Culture & Benefits

• Fully remote work with the ability to work from anywhere.
• One-time home-office setup allowance and company-provided equipment.
• Stock options and a health plan available wherever the role is based.
• Flexible days off.
• Language, professional, and personal development courses.