Senior AI Reliability Engineer

EPAM, Київ, Харків, Львів, Дніпро, Одеса, Вінниця, Івано-Франківськ

Що робити

Instrument production LLM, RAG and agentic applications with AI telemetry based on OpenTelemetry and APM-native AI monitoring
Implement distributed tracing across multi-model chains, agent workflows and retrieval-augmented generation pipelines to profile systemic latency and failure points
Define and measure AI-native SLIs and SLOs: time to first token (TTFT), throughput, error and refusal rates, cost per request, semantic drift, hallucination boundaries, contextual accuracy
Set up structured semantic logging and prompt/response monitoring for quality analysis
Build and run evaluation loops for output quality and safety — golden sets, LLM-as-a-judge, Ragas/DeepEval-style frameworks — and wire them into CI/CD and runtime

4+ years in SRE, DevOps, platform or observability engineering, including hands-on work with production AI/ML or LLM workloads
Solid SRE fundamentals: Golden Signals, SLI/SLO definition, error budgets and burn rate, incident lifecycle, ITIL basics
Strong Python for instrumentation, automation and evaluation tooling
Practical experience with OpenTelemetry and at least one APM/observability platform: New Relic, Datadog, Grafana LGTM stack, Splunk or Elastic
Hands-on production experience with at least one cloud platform (Azure preferred, AWS or GCP) and Kubernetes

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