Sustaining Engineer - L4

Responsibilities

Communicate technical issues clearly to customers, engineers and senior stakeholders, including executive audiences.
Own complex customer escalations from diagnosis through to resolution, mitigation and RCA.
Lead live incident response, war rooms and cross-functional investigations with Engineering, QA and Field teams.
Debug complex distributed-systems, storage and performance issues across the system, protocol and application layers.
Reproduce customer issues and feed findings into product and reliability improvements.
Develop runbooks, troubleshooting guidance and performance-tuning practices.
Act as a technical authority on Infinia internals, mentoring engineers and influencing architectural best practice.
Partner with Field CTOs, Solutions Architects and Sales Engineers on strategic customer issues.
Use AI, automation and observability to improve diagnostics, reliability and MTTR.
Communicate technical issues clearly to customers, engineers and senior stakeholders, including executive audiences.
This position requires participation in an on-call rotation to provide after-hours support as needed.

Significant experience in enterprise storage, distributed systems or cloud infrastructure, with technical leadership at Senior or Staff level.
Deep understanding of file systems and storage technologies, including S3, POSIX, NFS and storage performance.
Strong Linux systems knowledge, including kernel-level troubleshooting and debugging.
Strong coding ability in Python or C++.
Proven ability to diagnose complex issues using tools such as strace, tcpdump and perf.
Genuine interest in working directly with customers and taking ownership of complex problems through to resolution.

Experience with DDN, VAST, Weka or similar scale-out storage/file systems.
Familiarity with observability platforms such as Prometheus, Grafana, ELK or OpenTelemetry.
Knowledge of replication, consistency models and data integrity mechanisms.
Experience supporting AI/ML, LLM training or other high-performance computing environments.
Experience using AI tools for log analysis, troubleshooting, automated RCA or reducing MTTR.