Senior Site Reliability Engineer

EPAM Systems; Poland; On-site; USD 140,000 - 210,000; Full time

Job summary

EPAM Systems seeks a Senior Site Reliability Engineer to own reliability and operability of production AI systems. You will bridge deployment and long-term operability while embedding cost, security, and quality discipline into every solution lifecycle.

You will own end-to-end deployments on Azure, including infrastructure as code, CI/CD pipelines, and environment management, ensuring environments are rebuildable from source.

Qualifications

• 5+ years operating cloud production systems with on-call experience
• Azure IaaS/PaaS expertise; IaC (Terraform/Bicep)
• LLM-aware observability; Python/Bash automation
• FinOps basics for AI workloads
• Familiarity with incident triage, runbooks, and postmortems

Responsibilities

• Own reliability and observability for production AI systems
• Define SLOs and manage cost, latency, and quality dashboards
• Lead incident management, runbooks, and blameless postmortems
• Oversee security posture, patching, and access reviews
• Collaborate with pods and architects on operability patterns

Tools

Terraform/Bicep

CI/CD tooling

Job description

Responsibilities

• We are seeking a Senior Site Reliability Engineer to own the reliability, observability, and operational health of production AI systems, bridging the gap between deployment and long-term operability while embedding cost, security, and quality discipline into every solution's lifecycle.


• Own deployment end-to-end, including infrastructure as code, CI/CD pipelines, and environment management on Azure, ensuring every environment is rebuildable from source


• Build LLM-aware observability with traces on every model call, production quality signals such as eval sampling, drift detection, and guardrail-trigger rates, plus cost and latency dashboards


• Define and defend SLOs covering availability, latency, and quality objectives per solution, balancing delivery speed against stability with data-driven error budgets


• Run incident management, including on-call models, runbooks written before incidents occur, and blameless postmortems afterward


• Manage the cost of intelligence by monitoring token economics per solution, wiring in budgets and alerts, and conducting capacity planning proactively


• Keep the security posture current through patching, secret rotation, access reviews, and audit readiness across the solution's entire lifecycle


• Shape operability requirements before handover, ensuring they land in the pod's definition of done, and run hypercare jointly with sign-off on what will be operated


• Feed operational patterns, failure modes, and cost learnings back to the pods and the Architect

Requirements

• 5+ years of experience operating cloud production systems, with a track record in scaling, defining SLOs, managing on-call rotations, and automating manual work away


• Expertise in Azure IaaS/PaaS operations, infrastructure as code (Terraform/Bicep), and CI/CD tooling


• Proficiency in observability stacks with LLM tracing, container orchestration, and Python/Bash automation


• Knowledge of FinOps basics for AI workloads


• Familiarity with daily AI use in operations work, including incident triage, runbook drafting, log analysis, and automation code