Director, Site Reliability Engineering
Salesforce · New York - New York ·
- Category
- SRE
- Experience
- 5+ years
- Company size
- 1000+
- Salary
- USD 197,300 – 344,700 / year
Salesforce · New York - New York ·
Lead a team to build and scale a proactive, automated SRE practice that embeds reliability, observability, and incident response into Salesforce’s AI-driven platform and services.
To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
Software EngineeringJob Details
About Salesforce
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Job Title: Director, Site Reliability Engineering
Location: New York, NY; San Francisco, CA; Dallas, TX
We are looking for a Director of Site Reliability Engineering to spearhead the evolution of our reliability, observability, and operational engineering capabilities.
In this role, you will transform our SRE function—moving our engineering organization from reactive incident response to a proactive, automated, and data-driven reliability culture. Partnering closely across Application Engineering, Platform, Architecture, Security, Infrastructure, and Product, you will ensure our services are resilient, observable, scalable, and production-ready long before they launch.
As an impactful people leader with sharp technical judgment, you will directly manage and empower a core team of ~6 engineers while driving cross-functional alignment across a complex organization. You won't just run existing playbooks; you will define the strategy, tooling, automation, and culture needed to mentor your team and scale system reliability enterprise-wide.
SRE Strategy and Leadership
Define and execute the long-term strategy and roadmap for Site Reliability Engineering.
Establish a clear operating model for SRE, including team scope, engagement models, ownership boundaries, and success measures.
Build and develop a high-performing team of site reliability and operations engineers.
Modernize the SRE function through automation, AI-assisted operations, self-service capabilities, and engineering-first practices.
Translate business priorities and customer impact into clear reliability investments and engineering outcomes.
Advise senior technology leaders on operational risk, resilience, capacity, and reliability tradeoffs.
Reliability Engineering
Establish service-level indicators, service-level objectives, error budgets, and reliability standards for critical services.
Partner with engineering teams to design reliability, scalability, recoverability, and graceful degradation into systems.
Define what it means for a service to be operationally and observably ready for production.
Develop readiness reviews and certification practices for high-impact services and launches.
Drive improvements in system availability, performance, resiliency, and recovery.
Ensure reliability requirements are incorporated throughout the software development lifecycle rather than addressed only after deployment.
Observability
Define an enterprise observability strategy spanning metrics, logs, traces, events, synthetics, real-user monitoring, and business telemetry.
Establish common instrumentation, telemetry, dashboards, alerting, and service-health standards.
Reduce fragmented or duplicative observability implementations by promoting shared patterns and reusable capabilities.
Improve end-to-end visibility across distributed systems, customer journeys, services, and infrastructure.
Partner with engineering teams to ensure telemetry is actionable, contextual, and tied to customer and business outcomes.
Establish governance and measurement to assess adoption and effectiveness of observability standards.
Incident Management and Operational Excellence
Improve incident detection, response, mitigation, communication, and learning.
Lead the transition from manual and reactive operations toward automated detection, diagnosis, remediation, and incident creation.
Reduce mean time to detect, acknowledge, mitigate, and recover.
Improve on-call practices, escalation paths, runbooks, and operational ownership.
Establish blameless post-incident review practices that produce measurable engineering improvements.
Identify recurring sources of operational toil and create plans to eliminate or automate them.
Partner with engineering leaders to ensure actions from incidents are prioritized and completed.
Automation and AI-Enabled Operations
Develop a roadmap for intelligent operations, including anomaly detection, event correlation, automated triage, assisted root-cause analysis, and remediation.
Evaluate opportunities to use agents and AI-assisted workflows across observability, incident response, capacity planning, and operational support.
Build automation that reduces cognitive load and improves the speed and consistency of operational decisions.
Ensure automation is safe, measurable, auditable, and designed with appropriate human oversight.
Promote platform and self-service approaches that allow product teams to adopt reliability practices with minimal friction.
Cross-Functional Partnership
Partner with engineering, DevOps, and business stakeholders.
Influence teams that do not directly report into SRE and build shared accountability for production outcomes.
Create clear service ownership models and operational expectations across teams.
Support major launches and critical business events through readiness planning, risk assessment, testing, and operational coordination.
Communicate reliability posture, risks, trends, and investments to executive and technical audiences.
Measures of Success
Improved availability and reliability of critical services.
Reduced time to detect, diagnose, mitigate, and recover from incidents.
Increased percentage of services meeting observability and production-readiness standards.
Reduced alert noise, operational toil, and manual incident-management activity.
Increased adoption of service-level objectives and measurable reliability practices.
Improved quality and completion rate of post-incident corrective actions.
Increased automation across detection, triage, remediation, and operational workflows.
Stronger ownership of production reliability across engineering teams.
Engineering-first and automation-oriented.
Comfortable challenging legacy operating models and assumptions.
Able to move between technical detail and executive-level strategy.
Outcome-focused, pragmatic, and data-driven.
Builds trust through clarity, accountability, and strong partnership.
Develops leaders and creates an inclusive, high-performance engineering culture.
Treats incidents as opportunities to improve systems rather than assign blame.
Brings urgency to operational risks while maintaining focus on sustainable solutions.
Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or a related technical field; Master’s degree or MBA preferred.
10+ years of progressive engineering experience, including 5+ years in engineering leadership managing SRE, Platform, or Systems Engineering teams
Proven experience building or transforming a reliability or operational engineering organization.
Strong understanding of distributed systems, cloud architecture, application architecture, networking, infrastructure, and software delivery.
Experience establishing observability, incident-management, service-level objective, and production-readiness practices.
Demonstrated ability to improve reliability through engineering and automation rather than process alone.
Proven experience leading teams responsible for highly available, customer-facing, or business-critical systems.
Strong understanding of modern telemetry, including metrics, logs, distributed tracing, synthetic monitoring, and real-user monitoring.
Demonstrated success driving alignment and building consensus across cross-functional engineering teams and executive stakeholders
Ability to balance immediate operational needs with long-term engineering transformation.
Strong written, verbal, and executive communication skills.
Strong experience operating large-scale systems in AWS or another major cloud environment.
Proven track record with observability platforms such as New Relic, Splunk, Datadog, Sentry, Honeycomb, Grafana, Prometheus, or OpenTelemetry.
Demonstrated experience implementing OpenTelemetry or common instrumentation standards.
Verified proficiency building internal developer platforms, paved roads, or self-service reliability capabilities.
Experience applying AI, machine learning, or agent-based automation to operational workflows.
Seasoned capability with chaos engineering, resilience testing, disaster recovery, capacity planning, and performance engineering.
Software engineering experience and the ability to engage deeply in architecture and design discussions.
Solid background in supporting high-profile launches, events, or systems with significant customer and business impact.
*LI-Y
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The typical base salary range for this position is $197,300 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $237,700 - $344,700 annually.

The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.