Lead Infrastructure Engineer Storage

Job responsibilities

• Uses enterprise-authorized AI capabilities within the work environment to accelerate infrastructure analysis and design documentation validating outputs and handling operational data according to sensitivity and security requirements.
• Applies reuse-first AI-assisted practices within delivery and automation routines to identify recurring issues and validate remediation options ensuring changes are traceable/auditable and aligned to resiliency and security expectations.
• Own and continuously improve SLOs/SLIs error budgets on-call readiness and operational excellence for storage services.
• Lead incident response for storage outages/performance degradations; drive RCAs and implement preventative actions.
• Create and maintain runbooks escalation paths and standardized operational procedures.
• Operate and enhance block/file/object storage platforms across on-prem and/or cloud environments.
• Perform performance tuning capacity planning lifecycle management and resiliency testing (failover/DR validation).
• Partner with infrastructure network OS database and application teams to meet workload requirements and reliability targets.
• Build automation for provisioning patching upgrades replication backup/restore and compliance checks.
• Implement AI-driven observability/AIOps (telemetry correlation anomaly/regression detection LLM-assisted incident/runbook workflows) with accuracy auditability and safe rollout.

Required qualifications capabilities and skills

• Formal training or certification on infrastructure engineering concepts and 5 years applied experience
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity.
• Ability to review and validate AI-assisted recommendations before implementation escalating when uncertain and ensuring outcomes align to resiliency security and auditability expectations.
• Strong knowledge of storage fundamentals (RAID/erasure coding replication snapshots tiering/caching IOPS/latency multipathing SAN/NAS object semantics).
• Hands-on experience with at least one major storage ecosystem (e.g. NetApp Dell EMC PowerStore/Isilon Pure Hitachi Ceph IBM or cloud storage services).
• Solid Linux fundamentals including system performance networking basics and kernel/storage-stack concepts.
• Strong scripting/programming in one or more of Python Go Bash.
• Experience with observability stacks (e.g. Prometheus/Grafana ELK/OpenSearch Splunk Datadog OpenTelemetry).
• Proven incident management skills and ability to operate effectively in an on-call rotation.
• Practical AI/data skills for operations (anomaly detection/forecasting/correlation/classification; feature extraction and evaluation; integrating AI into production tooling/CI/CD; safe LLM use with guardrails and human-in-the-loop review).

• Kubernetes storage (CSI) stateful workloads and container platform operations.
• Infrastructure as Code (Terraform/CloudFormation) and configuration management (Ansible/Chef/Puppet).
• Streaming/queue tooling for telemetry and event pipelines (e.g. Kafka).
• Experience with ITSM/event management platforms (e.g. ServiceNow).
• Backup/DR products and strategy design including RPO/RTO tradeoffs.
• Security controls for data platforms (KMS/HSM secrets management key rotation).
• Experience building/operating controlled self-service platforms with guardrails to reduce toil at scale.