Senior Site Reliability Engineer at Salesforce

Job description

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 Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we re looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce s core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. Salesforce is seeking a senior engineering candidate to join the Site Reliability organization in San Francisco. Working closely with counterparts in the Infrastructure and R&D organizations, this organization provides a global team of engineers monitoring cloud service availability and ready to swiftly repair any service-impacting issues. Five days a week, 24 hours a day, in a follow-the-sun model with weekend oncall, the Site Reliability team keeps the Salesforce cloud and our customers protected. The Experience As an SRE, you will be a technical leader of the team driving Salesforce’s operational resilience by engineering solutions that blend automation, observability, and AI-powered platforms. You will not only respond to incidents but proactively design systems that prevent them, applying software engineering principles to operations to reduce toil and improve reliability at scale. By leveraging cutting-edge software engineering practices within SRE function and AI-driven insights, you will help transform how services are built, monitored, and operated — ensuring that Salesforce delivers always-on, high-performance experiences to customers worldwide. Build and run reliable, scalable, and efficient systems by applying software engineering principles to operations. Our mission is to ensure services are highly available, performant, and resilient — while continuously improving the balance between operational work and engineering innovation. Reliability as the Priority : Ensure that systems meet defined Service Level Indicators (SLIs) and Service Level Objectives (SLOs), using error budgets to guide engineering and release decisions. Engineering for Operations : Apply software engineering practices — automation, monitoring, self-healing systems — to eliminate toil and improve operational efficiency. Incident Management : Lead the coordinated response to incidents as an Incident Commander, drive fast recovery (low TTR), and ensure lasting improvements through blameless postmortems. Continuous Improvement : Identify and remove sources of toil, enhance observability, and optimize systems to reduce Time to Detect (TTD) and Time to Restore (TTR). Collaboration with Development : Partner with product and engineering teams early in the lifecycle to design, build, and operate systems that are reliable by default. Long-Term Focus : Leverage AI-driven automation to eliminate manual workflows, enabling the team to focus on complex problem-solving and strategic innovation while reducing operational overhead to less than 20% of capacity. What You ll Actually Be Doing: Lead incident detection, response, and resolution—driving root cause analysis, postmortems, and proactive measures to ensure high uptime, rapid recovery, and prevention of future issues. Lead post-incident reviews, drive systemic fixes through corrective actions, and ensure customer-facing services maintain peak performance and reliability. Understanding of AI/ML concepts applied to operations (e.g., anomaly detection, predictive analysis). Independently drive the design and implementation of complex automation platforms, self-healing systems, and AI-powered operational tooling using durable workflow engines (Temporal, Airflow, Argo Workflows). Architect and build production-grade observability solutions — monitoring, logging, alerting, and tracing systems — that enable proactive detection and autonomous remediation. Design and implement AI/ML-powered operations tools including anomaly detection systems, predictive analysis pipelines, intelligent runbook automation, and prompt-engineered operational agents (MCP-based). Drive optimization of system performance, reliability, and cost-effectiveness through proactive monitoring and tuning. Ensuring that work carried out by the Site Reliability team is executed in such a way as to comply with the company’s internal compliance policy and directives. Identifying opportunities and driving the creation of comprehensive technical epics that include well-defined problem statements, detailed project and implementation documentation, and clearly measurable business outcomes aligned with team objectives. Provide technical coaching to junior team members through pair programming, design reviews, and code reviews — helping grow their skills and knowledge. Collaborate with engineering and product teams to define and uphold SLAs/SLOs, driving improvements in service reliability and customer experience. Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code. Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale. Critically evaluate code (Human or AI-generated) for correctness, quality, security, and performance Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably. You re Our Person If You Have: 5 years of experience in systems engineering and software engineering for large-scale, internet-facing services. Hands-on expertise with containerized architectures (Docker, Kubernetes) and orchestration platforms. Strong knowledge of distributed systems and Linux/Unix internals, with experience tuning performance and troubleshooting at scale. Familiarity with large-scale internet service architectures (DNS, HTTP, Load Balancing, caching, etc.). Proven proficiency in Python and Go (GoLang) with strong software engineering practices (testing, code review, CI/CD). Production experience building and operating observability platforms (Grafana, Prometheus, ELK, Splunk, Datadog, or similar) Solid background in incident management, including on-call participation, root cause analysis, and postmortem practices. Strong understanding of SRE principles: SLIs/SLOs, error budgets, toil reduction, blameless culture, and capacity planning. Hands-on experience with workflow/orchestration engines (Temporal, Airflow, Argo Workflows, or similar) for building durable automation pipelines. Experience applying AI/ML to operations — including anomaly detection, predictive analysis, LLM-based automation, and prompt engineering to build intelligent operational agents and workflows. Excellent communication skills with demonstrated ability to lead during high-pressure incidents, present technical designs to leadership, and mentor junior engineers. Track record of mentoring and technically coaching other engineers. Ability to work in a 24/7 global operations model, managing multiple priorities under time-sensitive conditions. Growth mindset with curiosity to explore new technologies and drive continuous improvement. A demonstrated, genuine AI-first approach to engineering. Using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty. Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in development workflows Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready. A related technical degree required. Even Better If You Have: Experience with AI agent frameworks, MCP (Model Context Protocol), or building LLM-powered operational tools. Contributions to open-source reliability/observability tooling. AWS/GCP professional-level certifications. Prior experience in SRE organizations supporting multi-cloud or hyperscale environments. Python and Go proficiency for systems-level tooling. Experience with chaos engineering and game day exercises. Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. Accommodations If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form . Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options. Posting Statement Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: salesforcebenefits.com.pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $148,500 - $223,900 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $246,000 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

Requirements

Must-haves

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 Engineering
Lead incident detection, response, and resolution—driving root cause analysis, postmortems, and proactive measures to ensure high uptime, rapid recovery, and prevention of future issues.
Lead post-incident reviews, drive systemic fixes through corrective actions, and ensure customer-facing services maintain peak performance and reliability.
Understanding of AI/ML concepts applied to operations (e.g., anomaly detection, predictive analysis).
Independently drive the design and implementation of complex automation platforms, self-healing systems, and AI-powered operational tooling using durable workflow engines (Temporal, Airflow, Argo Workflows).
Architect and build production-grade observability solutions — monitoring, logging, alerting, and tracing systems — that enable proactive detection and autonomous remediation.
Design and implement AI/ML-powered operations tools including anomaly detection systems, predictive analysis pipelines, intelligent runbook automation, and prompt-engineered operational agents (MCP-based).
Drive optimization of system performance, reliability, and cost-effectiveness through proactive monitoring and tuning.
Ensuring that work carried out by the Site Reliability team is executed in such a way as to comply with the company’s internal compliance policy and directives.
Provide technical coaching to junior team members through pair programming, design reviews, and code reviews — helping grow their skills and knowledge.
Collaborate with engineering and product teams to define and uphold SLAs/SLOs, driving improvements in service reliability and customer experience.
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
Critically evaluate code (Human or AI-generated) for correctness, quality, security, and performance
Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
5 years of experience in systems engineering and software engineering for large-scale, internet-facing services.
Hands-on expertise with containerized architectures (Docker, Kubernetes) and orchestration platforms.
Strong knowledge of distributed systems and Linux/Unix internals, with experience tuning performance and troubleshooting at scale.
Familiarity with large-scale internet service architectures (DNS, HTTP, Load Balancing, caching, etc.).
Proven proficiency in Python and Go (GoLang) with strong software engineering practices (testing, code review, CI/CD).
Production experience building and operating observability platforms (Grafana, Prometheus, ELK, Splunk, Datadog, or similar)
Solid background in incident management, including on-call participation, root cause analysis, and postmortem practices.
Strong understanding of SRE principles: SLIs/SLOs, error budgets, toil reduction, blameless culture, and capacity planning.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aidesign systemsmldockerkubernetespythongogolangci/cdllmawsgcp

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Parental Leave