2 months ago
Pune, IndiaStaff+
Responsibilities
- Own critical customer case escalations end-to-end through root-cause analysis, mitigation, and resolution.
- Lead technical responses for Infinia incidents, including war rooms, live incident bridges, and cross-functional collaboration.
- Troubleshoot complex system, protocol, and application issues across enterprise and hyperscale environments.
- Develop expertise in Infinia internals, metadata handling, storage fabric interfaces, performance tuning, and AI integration.
- Reproduce customer issues and recommend product improvements, workarounds, and reliability enhancements.
- Create and maintain runbooks, performance-tuning guides, and root-cause-analysis documentation.
- Partner with Field CTOs, Solutions Architects, Sales Engineers, Engineering, QA, and Field teams to support strategic customers.
- Use AI tools, observability, automation, and self-healing mechanisms to accelerate diagnostics and reduce MTTR.
- Translate technical findings into executive-ready summaries and business-impact statements.
- Deliver training to customer support and field engineering teams and participate in post-mortems and executive briefings.
Requirements
- At least 8 years of experience in enterprise storage, distributed systems, or cloud infrastructure support/engineering.
- Deep understanding of file systems and interfaces including S3, POSIX, and NFS, as well as storage performance and Linux kernel internals.
- Ability to script and code using Python, Go, and C++.
- Proven debugging experience at the system, protocol, and application levels using tools such as strace, tcpdump, and perf.
- Hands-on Linux troubleshooting experience.
- Exposure to RDMA, NVMe-oF, or high-performance networking stacks.
- Exceptional communication and executive-reporting skills.
- Experience using AI tools such as log-pattern analysis, LLM-based summarization, and automated RCA tooling to accelerate diagnostics and reduce MTTR.
- Experience with DDN, VAST, Weka, or similar scale-out file systems is preferred.
- Strong scripting or coding ability in Python, Bash, or Go is preferred.
- Familiarity with Prometheus, Grafana, ELK, or OpenTelemetry is preferred.
- Knowledge of replication, consistency models, and data-integrity mechanisms is preferred.
- Exposure to Sovereign AI, LLM model-training environments, or autonomous-system data architectures is preferred.
- Willingness to participate in an on-call rotation for after-hours support is required.
Benefits
- The role includes participation in an on-call rotation to provide after-hours support as needed.
About DDN
DDN builds high-performance data storage and data management systems for AI, machine learning, and high-performance computing workloads used by enterprises, research institutions, and governments. It sells appliance hardware and software (including parallel file systems and AI data platforms) along with support and professional services. Founded in 1998 and headquartered in Chatsworth, California, the privately held company reports serving over 11,000 organizations worldwide.