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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