Senior Director of Site Reliability Engineering - Executive Director

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As a Senior Director of Site Reliability Engineering at JPMorgan Chase in Infrastructure Platforms, you own and lead the SRE organization for our global network estate. You build and run teams of code-first SREs embedded within the network engineering teams, making reliability an engineered property of every platform rather than an operational afterthought. You are accountable for the reliability of enterprise-scale infrastructure: the SLIs/SLOs it is held to, the observability that proves it, the incident leadership that protects it, and the automation that engineers away toil. You lead an AI-native organization, driving fluent use of AI across the software development and operations lifecycle while holding the line on correctness, security, and risk.
Job Responsibilities
Owns the reliability of the network estate end-to-end: define the SRE operating model, the embedded-team structure, and the reliability outcomes the organization is accountable for
Builds, leads, and grows a multi-team SRE organization: hire and develop SRE managers and senior individual contributors, and set a high, consistent code-first engineering bar across teams
Runs the embedded model: place SRE teams inside the network engineering teams so reliability is engineered in at the source, while maintaining a coherent central discipline, shared standards, and career path
Establishes and govern SLIs, SLOs, and error budgets across platforms; drive SLO-based alerting, telemetry standards, and actionable observability as organizational defaults
Sets the strategy for toil reduction and self-healing infrastructure: treat repeated manual work as a defect to be engineered out, and hold teams to measurable reduction
Acts as the bridge between the network engineering teams and the automation-platform and data-engineering teams: translate operational reliability needs into platform and data requirements, and ensure the resulting tooling and data actually meet the business need and are adopted in production
Owns the major-incident and post-incident practice: strong incident leadership, blameless post-incident reviews, and durable engineering fixes that actually land
Drives an AI-native way of working across the org (AI-assisted development, code review, test generation, incident and root-cause analysis) with clear validation standards, so speed never compromises correctness, security, or reliability
Partners with network engineering, platform, and security leadership to align reliability strategy, roadmaps, and investment, and make the case for reliability work in business terms
Applies security and operational-risk judgment across the engineering lifecycle and ensure the organization operates within a regulated-enterprise control environment
Leads firmwide reuse-first adoption of enterprise-authorized AI capabilities within the work environment to accelerate reliability planning, operational learning, and delivery execution, with human-in-the-loop validation and appropriate handling of sensitive data
Required Qualifications, Capabilities, and Skills
Extensive experience leading SRE, production engineering, or reliability-focused software organizations at scale, including leading other managers (a leader of leaders)
A code-first foundation: credible software engineering background and the judgment to hold a code-first SRE bar, not an operations-only one
Proven track record running production systems at scale, including SLI/SLO/error-budget practice, incident leadership, and measurable toil reduction
Demonstrated ability to build and scale teams: hiring, developing SRE leaders and senior engineers, and establishing engineering culture and career paths
Demonstrated experience leading safe adoption of enterprise-authorized AI capabilities within the work environment at firm scale, including validation practices, data sensitivity considerations, and measurable reliability outcomes
Deep observability and reliability expertise: white-box/black-box monitoring, SLO-based alerting, and telemetry, and the ability to set these as organizational standards
Strong systems thinking across interfaces, contracts, failure modes, and interactions at enterprise scale
Fluency and conviction in AI-native engineering: directing AI to do real engineering and operations work, with sound judgment on where it applies and where deep human expertise is required
Security-first mindset and sound operational-risk judgment from design through production
Able to influence across a large, matrixed organization and lead calmly under pressure during high-severity events
Outcome orientation: focused on reliability, impact, and cost, not activity or span of control
Preferred Qualifications, Capabilities, and Skills
Networking depth (routing, switching, security, packet/flow analysis) or experience leading reliability for network or network-adjacent platforms: a strong plus, not a requirement
Experience running an embedded SRE model, driving reliability into engineering teams from within rather than from a central operations silo
Experience across multiple infrastructure domains
Demonstrated use of AI to redesign engineering and operational workflows for measurable impact, and to build organizational AI fluency
Experience supporting mission-critical systems in a production environment
Prior experience in regulated or large-scale enterprise environments