Lead Infrastructure Engineer - Storage

Infrastructure Engineer - Storage
Job Description
Assume a vital position as a key member of a high-performing team that delivers infrastructure and performance excellence. Your role will be instrumental in shaping the future at one of the world's largest and most influential companies.
As an Infrastructure Engineer at JPMorgan Chase within the Enterprise Technology, Infrastructure Platforms team, you apply deep knowledge of software, applications, and technical processes within the infrastructure engineering discipline. Continue to evolve your technical and cross-functional knowledge outside of your aligned domain of expertise.
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).
Expertise in product and Infrastructure Support.
Hands-on experience with at least one or more 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; f