Senior Staff SRE Engineer (AI)

TL;DR

Senior Staff SRE Engineer (AI): Designing and operating scalable, resilient infrastructure for an agentic labor platform with an accent on Kubernetes, AWS, and MLOps. Focus on productionising ML models, enhancing CI/CD pipelines, and ensuring high availability for global enterprise customers.

Location: Remote (Must be based in the Europe Timezone)

Company

hirify.global builds the world’s first Agentic Labor Infrastructure to enable humans and AI agents to operate together as a unified, hybrid workforce.

What you will do

• Architect, deploy, and operate scalable, secure production environments on AWS.
• Design and evolve Kubernetes-based infrastructure, including migration and optimization initiatives.
• Define and operationalise SLIs, SLOs, and error budgets to drive reliability across engineering streams.
• Optimize end-to-end CI/CD pipelines to improve release safety and deployment frequency.
• Support and productionise ML workloads using MLOps practices, including model deployment and monitoring.
• Lead incident response for complex cross-system failures and mentor engineers to raise the reliability bar.

Requirements

• Extensive hands-on experience in SRE or Production Engineering roles.
• Deep expertise in AWS or Azure-based cloud infrastructure.
• Strong experience with Kubernetes scaling and production hardening.
• Advanced proficiency with Infrastructure-as-Code tools like Terraform.
• Experience supporting production data platforms and ML systems.
• Must be able to work within the Europe Timezone.

Nice to have

• Experience with NLP or LLM-based products.
• Background in enterprise environments with strict security and compliance requirements.
• Experience collaborating with large-scale enterprise customers to deploy environments within their VPCs.

Culture & Benefits

• High-performing global team with a strong ownership mentality and accountability.
• Opportunity to work with experts from Deepmind, Google, Amazon, and Miro.
• Fast-paced environment focused on data-aware decisions and delivering real customer value.
• Culture of continuous improvement and learning.