Site Reliability Engineer (AI)

Madiff; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Competitive salary

Multinational environment

Healthcare coverage

Long-term contract

Fully remote

Job summary

Madiff is seeking a Senior Site Reliability Engineer for a fully remote role supporting AI platforms. You will build and maintain the central monitoring layer, define SLIs and dashboards, and manage incidents to ensure stable, scalable production systems.

Work closely with engineering teams to improve release quality, standardise telemetry, and optimise CI/CD pipelines in a distributed cloud environment. This is a hands-on, ownership-driven role with a focus on reliability.

Qualifications

• 5+ years of experience in SRE, Platform, or Production Engineering.
• Hands-on experience with Kubernetes in production environments.
• Experience with Azure and Azure DevOps.
• Experience with monitoring tools such as Datadog.
• Strong incident management and root cause analysis skills.

Responsibilities

• Build and maintain central monitoring and alerting layer for AI applications and pipelines.
• Define and implement SLIs, alerts, and operational dashboards.
• Manage incidents including triage, coordination, root cause analysis, and prevention.
• Standardise telemetry across systems including latency, throughput, and failures.
• Optimise CI/CD pipelines and introduce quality gates for reliability.
• Work closely with engineering teams to reduce recurring issues and improve stability.

Skills

Kubernetes

Incident management

Root cause analysis

Monitoring

CI/CD

Tools

Datadog

Azure DevOps

Grafana

Job description

This is a remote position. We are looking for a Senior Site Reliability Engineer to support advanced AI platforms responsible for production-grade applications and pipelines. The role focuses on building and maintaining reliability, scalability, and operational excellence across multiple AI-driven systems. The engineer will work on a central operational layer for monitoring and managing AI workloads, improving system stability, and reducing incidents. This is a hands-on role requiring direct involvement in diagnosing production issues, implementing fixes, and optimising monitoring, alerting, and CI/CD processes. The position requires close collaboration with engineering teams to improve release quality, standardise telemetry, and ensure stable and predictable system behaviour in a distributed cloud environment.

Responsibilities

• Build and maintain central monitoring and alerting layer for AI applications and pipelines
• Define and implement SLIs, alerts, and operational dashboards
• Manage incidents including triage, coordination, root cause analysis, and prevention
• Standardise telemetry across systems including latency, throughput, and failures
• Optimise CI CD pipelines and introduce quality gates for reliability
• Work closely with engineering teams to reduce recurring issues and improve stability

Requirements

• Minimum 5+ years of experience in SRE, Platform, or Production Engineering
• Strong hands on experience with Kubernetes and production environments
• Experience with Azure and Azure DevOps
• Experience with monitoring tools such as Datadog
• Strong understanding of incident management and root cause analysis
• Ability to build practical monitoring and alerting systems

Nice to have

• Experience with AI or LLM pipelines
• Experience building monitoring platforms across multiple systems
• Experience with Grafana
• Experience working in large scale or distributed environments

Expectations

• Strong ownership mindset and accountability for system stability
• Proactive approach to identifying risks and improvements
• Hands on engineer actively working with systems, not only coordinating
• Comfortable working in dynamic and evolving environments

Benefits

• Solid, competitive salary
• Work in a multinational environment on international projects
• Comprehensive healthcare
• Long-term B2B contract with a stable project pipeline
• Work model: fully remote