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Software Engineering SMTS

Salesforce

Skills

Required

  • reliability / observability
  • Python
  • Go
  • incident management
  • SRE
  • code review
  • CI/CD
  • containerized architectures
  • Docker
  • Kubernetes
  • workflow/orchestration engines
  • Airflow
  • Prometheus

Preferred

  • AI agent frameworks
  • MCP
  • Model Context Protocol
  • LLM-powered
  • AI
  • AI/ML
  • Claude Code
  • GitHub
  • Copilot
  • Codex

Join Salesforce as a Software Engineering SMTS, where you will be a technical leader driving operational resilience through automation, observability, and AI-powered platforms. You will proactively design systems to prevent incidents, apply software engineering principles to operations, and ensure high availability and performance for customers worldwide. Your responsibilities will include incident management, continuous improvement, collaboration with development teams, and long-term focus on AI-driven automation.

Responsibilities

  • Conduire la résilience opérationnelle de Salesforce en concevant des systèmes qui préviennent les incidents.
  • Appliquer des pratiques d'ingénierie logicielle pour automatiser, surveiller et améliorer l'efficacité opérationnelle.
  • Diriger la réponse coordonnée aux incidents en tant que Commandant d'incident, en assurant une récupération rapide.
  • 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

Requirements

  • 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)
  • 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

Preferred

  • Experience with AI agent frameworks, MCP (Model Context Protocol), or building LLM-powered operational tools

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