Senior HPC Reliability Engineer – Multi-Cloud AI Ops

EPAM Systems Inc; Seattle (WA); Remote; USD 155,000 - 175,000; Full time

Benefits offered by this job

Medical Insurance

HSA

PTO

Paid Holidays

401(k) Plan

Employee Stock Purchase

Job summary

EPAM Systems, Inc. is seeking an engineer with HPC and site-reliability experience to keep a growing multi-cloud AI infrastructure reliable and efficient.

You will investigate hard operational problems across compute, accelerators, scheduling, storage, and networking, and translate findings into proactive detection and automated remediation using AI-powered agents. Success comes from understanding HPC production behavior and quickly learning unfamiliar systems.

Qualifications

• Operations experience with production HPC or large-scale distributed compute in reliability-focused role.
• Strong Linux and networking skills, debugging across processes, containers, storage I/O, DNS, connectivity, authentication.
• Correlates telemetry across multiple cloud environments using Prometheus, Grafana, OpenTelemetry, or centralized logging.
• Writes and maintains automation in Python or Go and has owned complex production investigations end-to-end.

Responsibilities

• Build understanding of multi-cloud HPC architecture and keep it current as infra changes.
• Proactively find reliability and performance problems by correlating logs, metrics, and events across clouds.
• Diagnose complex issues end-to-end across Linux hosts, containers, schedulers, and accelerators, identifying root causes.
• Turn investigations into repeatable tooling and agent-enabled workflows with safety checks and approvals.
• Strengthen observability and measurement of automation effectiveness and partner with cross-functional teams to implement durable fixes.

Skills

HPC operations

Linux networking

Telemetry correlation

Automation scripting

Tools

Prometheus

Grafana

OpenTelemetry

Centralized logging

Job description

EPAM Systems, Inc. is seeking an engineer with HPC and site-reliability experience to keep a growing multi-cloud AI infrastructure reliable and efficient.

You will investigate hard operational problems across compute, accelerators, scheduling, storage, and networking, and translate findings into proactive detection and automated remediation using AI-powered agents. Success comes from understanding HPC production behavior and quickly learning unfamiliar systems.