Software Engineering SMTS

• 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
• Lead incident detection, response, and resolution — driving root cause analysis, postmortems, and systemic fixes to ensure high uptime and rapid recovery
• Independently drive the design and implementation of automation platforms and self-healing systems using durable workflow engines (Temporal, Airflow, Argo Workflows)
• Architect and build production-grade observability solutions — monitoring, logging, alerting, and tracing — that enable proactive detection and autonomous remediation
• Design and implement AI/ML-powered operations tools, including anomaly detection, predictive analysis, intelligent runbook automation, and MCP-based operational agents
• Partner with engineering and product teams to define and uphold SLAs/SLOs, and coach junior engineers through pair programming, design reviews, and code reviews

Benefits

• Medical Care
• Life Insurance
• Retirement Savings
• Employee Assistance Programs
• With 9 standard holidays and four floating holidays, you get a total 13 paid days off each year

• An AI-first approach to engineering, with experience applying AI/ML to operations and using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor) in development workflows
• Proven proficiency in Python and Go (GoLang) with strong software engineering practices (testing, code review, CI/CD)
• Hands-on expertise with containerized architectures (Docker, Kubernetes) and workflow/orchestration engines (Temporal, Airflow, Argo Workflows, or similar)
• Production experience building and operating observability platforms (Grafana, Prometheus, ELK, Splunk, Datadog, or similar)
• Solid background in incident management and SRE principles: on-call, root cause analysis, postmortems, SLIs/SLOs, error budgets, and toil reduction
• 5+ years of experience in systems and software engineering for large-scale, internet-facing services, with strong knowledge of distributed systems, Linux/Unix internals, and internet architectures (DNS, HTTP, load balancing, caching)
• Experience with AI agent frameworks, MCP (Model Context Protocol), or building LLM-powered operational tools
• Contributions to open-source reliability/observability tooling; experience with chaos engineering and game day exercises
• AWS/GCP professional-level certifications
• Prior experience in SRE organizations supporting multi-cloud or hyperscale environments; Python and Go proficiency for systems-level tooling