site reliability engineer

4 dni temu

Warszawa, Województwo mazowieckie, Polska Enfint Pełny etat 180 000 zł - 280 000 zł/rok

Bezpłatnie za pośrednictwem poczty elektronicznej lub Google

Zapisz tę ofertę pracy i uporządkuj wyszukiwanie

Utwórz bezpłatne konto, aby zapisywać oferty pracy, tworzyć alerty i wracać do tego ogłoszenia ze swojego pulpitu nawigacyjnego.

Bezpłatnie za pośrednictwem poczty elektronicznej lub Google

Kontynuując, akceptujesz nasze Warunki & Politykę prywatności.

EPAM develops enterprise software products, open source solutions, and accelerators, including solutions for production AI systems.

Own end-to-end deployment, including infrastructure as code, CI/CD pipelines, and environment management on Azure
Build LLM-aware observability with model-call traces, production quality signals, drift detection, guardrail-trigger rates, and cost and latency dashboards
Define and defend SLOs for availability, latency, and quality objectives, balancing delivery speed against stability with data‑driven error budgets
Run incident management, including on‑call models, pre‑incident runbooks, and blameless postmortems
Manage intelligence costs by monitoring token economics, configuring budgets and alerts, and conducting proactive capacity planning
Maintain the security posture through patching, secret rotation, access reviews, and audit readiness across the solution lifecycle
Shape operability requirements before handover and ensure their inclusion in the pod's definition of done
Run hypercare jointly and sign off on what will be operated
Feed operational patterns, failure modes, and cost learnings back to the pods and the Architect

5+ Years of experience operating cloud production systems, including scaling, defining SLOs, managing on-call rotations, and automating manual work
Expertise in Azure IaaS/PaaS operations, infrastructure as code with Terraform/Bicep, and CI/CD tooling
Proficiency with observability stacks, LLM tracing, container orchestration, and Python/Bash automation
Knowledge of FinOps basics for AI workloads
Familiarity with daily AI use in operations, including incident triage, runbook drafting, log analysis, and automation code

No conditions specified