Technology Support Lead

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Corporate Sector

This role focuses on leveraging enterprise-authorized AI capabilities to enhance production application support, aiming to improve incident triage speed and consistency. The lead will oversee the operational stability, availability, and performance of production systems, using AI tools for tasks like synthesizing operational signals and validating AI-assisted recommendations. The role requires strong validation habits, awareness of data sensitivity, and experience with observability and incident management in large-scale technology environments.

What you'd actually do

  1. Leads team adoption of enterprise-authorized AI capabilities within the work environment to improve incident triage speed and consistency (e.g., synthesizing operational signals into prioritized actions), with human-in-the-loop validation and appropriate handling of sensitive data.
  2. Applies reuse-first, AI-assisted practices across incident/problem/change routines to identify recurring interruption patterns and validate remediation actions aligned to resiliency and security expectations.
  3. Provides end-to-end application and infrastructure service delivery to enable successful business operations of the firm
  4. Supports the day-to-day maintenance of the firm’s systems to ensure operational stability and availability
  5. Analyze complex situations and trends to anticipate and solve incident, problem, and change management in support of full stack technology systems, applications, or infrastructure.

Skills

Required

  • 8+ years of experience or equivalent expertise troubleshooting, resolving, and maintaining information technology services
  • Experience managing applications or infrastructure in a large-scale technology environment both on premises and public cloud
  • Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support production operations workflows with strong validation habits and awareness of data sensitivity.
  • Ability to review and validate AI-assisted incident recommendations before action, escalating when uncertain and ensuring outcomes align to operational, security, and auditability expectations.
  • Experience in observability and monitoring tools and techniques, setting them up for large scale applications and services.
  • Incident management – experienced in production incident management, root cause analysis (RCA) and related follow ups to ensure closure of the issue
  • Role implies collaboration with all levels of seniority including the developers, business users and global production management teams.
  • Hands on experience on scripting language, any programming language and debugging for production issue and system automations.
  • Hands on experience with private/public cloud, Kubernetes or equivalent.
  • Strong understanding of infrastructure costing, with the ability to apply tuning mechanisms that optimize both performance and cost efficiency.
  • Experience with ServiceNow platforms

Nice to have

  • Understanding of software life cycle development
  • Knowledge of document management system

What the JD emphasized

  • Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support production operations workflows with strong validation habits and awareness of data sensitivity.
  • Ability to review and validate AI-assisted incident recommendations before action, escalating when uncertain and ensuring outcomes align to operational, security, and auditability expectations.

Other signals

  • AI-assisted incident recommendations
  • synthesizing operational signals into prioritized actions
  • human-in-the-loop validation
  • reuse-first, AI-assisted practices