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Salary
$215k – $409k per year (Estimated)
Location
In office (New York)
Seniority
Staff · 7+ years exp
Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

Join us in a pivotal role where your deep expertise drives operational excellence and a step-change modernization of technology controls for an agentic environment-enhancing system stability, audit readiness, and engineering velocity across full stack technologies.

As a Technology Support Director, Tech Control Transformation Lead (Agentic) in the Consumer & Community Bank Technology team, you will lead teams ensuring the operational stability, availability, and performance of our production services while redesigning how controls operate in AI-enabled workflows. You will set strategic direction, influence across engineering, operations, and control partners, and modernize “how we prove it” through automation, instrumentation, traceability, and controls-as-code-reducing manual effort and repeat issues while improving prevention and continuous monitoring.

Job responsibilities

  • Directly manage multiple areas with strategic and transactional focus to enable technology support teams to deliver end-to-end application or infrastructure service delivery for the successful business operations of the firm
  • Lead the transformation from reactive remediation to a productized control operating model with clear intake, prioritization, delivery, validation, and durable closure mechanics across support processes
  • Redesign technology controls for an agentic environment, shifting from human-only checkpoints to controls that assume AI agents can generate artifacts, recommend actions, and execute workflows with appropriate guardrails and accountability
  • Set reuse-first expectations for enterprise-authorized AI adoption within the work environment across support operations to accelerate incident insights and operational reporting, with human-in-the-loop validation and appropriate handling of sensitive data
  • Establish governance standards for AI-assisted workflows used in incident/problem/change processes (including documentation and trend analysis), ensuring traceability/auditability and alignment to resiliency and security expectations
  • Develop and oversee policies and procedures to ensure operational stability and availability and oversee incident, problem, and change management in support of full stack technology systems, applications, or infrastructure
  • Modernize evidence, traceability, and auditability through controls-as-code patterns, automated evidence capture, and continuous control signals rather than manual attestation
  • Develop and oversee monitoring of production environments for anomalies, address issues, lead evolution utilizing standard observability tools, and ensure issues and solutions are appropriately escalated and communicated with business and technology stakeholders throughout resolution until service is restored
  • Establish reusable control patterns and embedded guardrails across domains such as identity and access, change controls, operational resilience, monitoring/alerting, configuration management, data controls, and third-party/tooling controls
  • Define and operationalize outcome-focused operating rhythms (working groups, prevention forums, and metric routines) that remove blockers, drive root-cause elimination, and measurably improve control and service performance

Required qualifications, capabilities, and skills

  • 7+ years of experience or equivalent expertise troubleshooting, resolving, and maintaining information technology services
  • Demonstrated experience leading safe use of enterprise-authorized AI capabilities within the work environment within production support workflows, including validation practices and awareness of data sensitivity
  • Ability to define review/approval, escalation, and accountability expectations for AI-assisted recommendations while maintaining operational, security, resiliency, and auditability outcomes
  • Experience managing applications or infrastructure in a large-scale technology environment both on premises and public cloud
  • Proficient in observability and monitoring tools and techniques
  • Demonstrated experience executing on processes in scope of the Information Technology Infrastructure Library (ITIL) framework
  • Demonstrated ability to drive control modernization using engineering-first approaches such as automation-by-default, measurable feedback loops, and root-cause elimination
  • Strong command of technology risk and control environments, including issue management, audit readiness, evidence standards, and sustainable operating controls

Preferred qualifications, capabilities, and skills

  • Experience designing and implementing controls-as-code / policy-as-code, automated guardrails embedded in CI/CD, and automated evidence capture for audit-ready traceability
  • Demonstrated success shifting organizations from after-the-fact reporting to proactive prevention and continuous monitoring, including reduced repeat issues and reopened findings
  • Experience establishing practical standards across issue/risk workflows and tooling (e.g., Jira-based workflows, inventories, break reduction, evidence management) with clear ownership from issue to outcome
  • Credible fluency with agentic development and AI-enabled workflows, including designing control approaches for agent actions, tool usage, provenance, and model risk
  • Executive-level communication skills, including translating control health into trusted metrics, decision points, and leading indicators aligned to business outcomes
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