Lead Infrastructure Engineer - Storage

JPMorgan Chase & Co.; Houston (TX); On-site; USD 130,000 - 180,000; Full time

Job summary

JPMorganChase is seeking a Lead Infrastructure Engineer within Enterprise Technology, Infrastructure Platforms. You will shape storage and infrastructure strategy, drive AI-assisted operations, and collaborate across teams to meet reliability targets.

The role emphasizes on-call readiness, automation, and security-focused design across on-prem and cloud environments. Suitable for senior engineers with deep storage and Linux foundations.

Qualifications

• Formal training or certification on infrastructure engineering concepts and 5+ years applied experience.
• Experience using enterprise-authorized AI capabilities to support infrastructure workflows with strong validation habits.
• Ability to review and validate AI-assisted recommendations before implementation with focus on resiliency and auditability.

Responsibilities

• Uses enterprise AI capabilities to accelerate infrastructure analysis and validation of design outputs.
• Applies AI-assisted practices to identify recurring issues and ensure changes are traceable and secure.
• Owns and improves SLOs/SLIs, error budgets, and on-call readiness for storage services.
• Lead incident response for storage outages and drive RCAs with preventative actions.
• Create and maintain runbooks, escalation paths, and standard operating procedures.
• Operate and enhance on-prem and cloud storage platforms (block/file/object).
• Perform performance tuning, capacity planning, lifecycle management, and DR testing.
• Collaborate with multiple teams to meet workload reliability targets.
• Build automation for provisioning, patching, upgrades, replication, backup/restore, and compliance.

Skills

Infrastructure engineering

AI in work environment

Linux fundamentals

Scripting (Python/Go/Bash)

Observability tooling

Incident management

On-call readiness

Storage fundamentals

Kubernetes storage

Education

Infrastructure engineering certification

Tools

Prometheus/Grafana

ELK/OpenSearch

Splunk

Datadog

OpenTelemetry

NetApp

Dell EMC PowerStore/Isilon

Ceph

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 a Lead Infrastructure Engineer at JPMorganChase 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).
• 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).

Preferred qualifications, capabilities, and skills

• 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.