Senior Lead Infrastructure Engineer - Mainframe

JPMorgan Chase & Co.; Kentucky; On-site; USD 120,000 - 180,000; Full time

Job summary

JPMorganChase & Co. is seeking a Senior Lead Infrastructure Engineer to shape and optimize enterprise batch scheduling and automation within Infrastructure Platforms.

You will administer CA-7, Control-M, and ZEKE, develop automation in REXX and Python, and drive mainframe modernization efforts across public and private clouds. You will troubleshoot batch runs, implement governance, and collaborate with cross-functional teams to deliver reliable, compliant operations with strong documentation and

Qualifications

• 5+ years of experience in mainframe systems programming and/or mainframe operations engineering in an enterprise environment.
• Hands-on expertise with CA-7, Control-M, and/or ZEKE.
• Strong coding/scripting skills in REXX and/or Python (with demonstrated automation deliverables).
• Strong troubleshooting skills across batch execution lifecycle (JCL errors, dataset/space issues, dependency problems, scheduling conflicts, restart/recovery).
• Working knowledge of core mainframe concepts such as JCL, JES, catalogs/datasets, SMP/E concepts, and operational controls.

Responsibilities

• Administer, configure, and support enterprise batch scheduling platforms (CA-7, Control-M, and/or ZEKE) including calendars, workload definitions, dependencies, SLA management, and automation.
• Design and implement batch workload standards, governance, and operational controls (job naming, restart/recovery, notifications, and escalation).
• Build and maintain automation solutions using REXX and/or Python to streamline operations (dataset management, job orchestration, health checks, reporting, and runbook automation).
• Diagnose and resolve batch failures, performance bottlenecks, and scheduling conflicts; perform root-cause analysis and implement preventative improvements.
• Integrate scheduling and automation with enterprise tooling (monitoring/alerting, ticketing, change management, audit evidence capture).
• Drive mainframe modernization initiatives, including API enablement, workflow standardization, and automation-first operating practices.
• Apply AI-assisted approaches to improve productivity and reliability (log analysis, anomaly detection, runbook generation, code assistance), while ensuring outputs are validated and compliant with applicable controls.
• Create and maintain high-quality documentation: procedures, automation code, runbooks, architectural diagrams, and knowledge base articles.
• Uses enterprise-authorized AI capabilities within the work environment to accelerate analysis of complex infrastructure signals and documentation of mitigation options, validating outputs and handling operational data according to sensitivity and security requirements.
• Drives thought leadership within the product line.
• Leads reuse-first adoption of AI-assisted practices across delivery and automation routines to reduce recurring issues, ensuring changes are validated, traceable and auditable, and aligned to resiliency and security expectations.

Skills

Mainframe systems programming

Batch scheduling

REXX

Python

JCL

JES

Cloud infrastructure

AI-assisted practices

Tools

CA-7

Control-M

ZEKE

Job description

Become a member of a team where you can contribute significantly to shaping the future of a world-renowned and influential company. Among top performers, you can make a direct and meaningful impact.

As a Senior Lead Infrastructure Engineer at JPMorganChase within the Infrastructure Platforms, you exhibit both depth and breadth of knowledge regarding software, applications, and technical processes across multiple technical disciplines. You also have a specialization in a specific domain within infrastructure engineering to drive programs or initiatives consisting of multiple technologies and applications.

Job responsibilities

• Administer, configure, and support enterprise batch scheduling platforms (CA-7, Control-M, and/or ZEKE) including calendars, workload definitions, dependencies, SLA management, and automation.
• Design and implement batch workload standards, governance, and operational controls (job naming, restart/recovery, notifications, and escalation).
• Build and maintain automation solutions using REXX and/or Python to streamline operations (e.g., dataset management, job orchestration, health checks, reporting, and runbook automation).
• Diagnose and resolve batch failures, performance bottlenecks, and scheduling conflicts; perform root-cause analysis and implement preventative improvements.
• Integrate scheduling and automation with enterprise tooling (monitoring/alerting, ticketing, change management, audit evidence capture).
• Drive mainframe modernization initiatives, including API enablement, workflow standardization, and automation-first operating practices.
• Apply AI-assisted approaches to improve productivity and reliability (e.g., log analysis, anomaly detection, runbook generation, code assistance), while ensuring outputs are validated and compliant with applicable controls.
• Create and maintain high-quality documentation: procedures, automation code, runbooks, architectural diagrams, and knowledge base articles.
• Uses enterprise-authorized AI capabilities within the work environment to accelerate analysis of complex infrastructure signals and documentation of mitigation options, validating outputs and handling operational data according to sensitivity and security requirements.
• Drives thought leadership within the product line.
• Leads reuse-first adoption of AI-assisted practices across delivery and automation routines to reduce recurring issues, ensuring changes are validated, traceable and auditable, and aligned to resiliency and security expectations.

Required qualifications, capabilities, and skills

• 5+ years of experience in mainframe systems programming and/or mainframe operations engineering in an enterprise environment.
• Hands-on expertise with CA-7, Control-M, and/or ZEKE
• Strong coding/scripting skills in REXX and/or Python (with demonstrated automation deliverables).
• Strong troubleshooting skills across batch execution lifecycle (JCL errors, dataset/space issues, dependency problems, scheduling conflicts, restart/recovery).
• Working knowledge of core mainframe concepts such as JCL, JES, catalogs/datasets, SMP/E concepts, and operational controls.
• Experience with change management, incident/problem management, and on-call support in regulated/controlled environments.
• Excellent communication skills with the ability to translate complex technical issues into clear operational guidance.
• Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations.
• Deep knowledge of cloud infrastructure and multiple cloud technologies (ability to operate in and migrate across public and private clouds)