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Sr. Software Engineer, Cloud Infrastructure - Slack

Job in Washington, District of Columbia, 20022, USA
Listing for: Salesforce
Full Time position
Listed on 2026-06-12
Job specializations:
  • Software Development
    Cloud Engineer - Software, DevOps
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

What You Will Be Doing

  • Lead software projects end-to-end — from scoping and architecture through delivery, iteration, and long-term ownership
  • Architect and build a next-generation internal platform that gives engineering teams a powerful foundation to innovate quickly
  • Deliver cutting-edge solutions leveraging containerization, virtualization, and a broad suite of AWS services
  • Author, extend, and improve Terraform modules that power infrastructure-as-code across Slack
  • Design and implement an in-house system to deploy, manage, and scale applications for service owners
  • Partner directly with development teams to identify performance bottlenecks and drive cloud efficiency improvements
  • Build strong, trusted relationships with service owners — serving as a go-to advisor on cloud architecture and best practices
  • Champion a culture of platform efficiency by sharing knowledge, writing runbooks, and leading internal enablement sessions
  • Mentor and grow junior engineers, scaling the impact of the team through thoughtful technical leadership
  • Make a measurable financial impact — driving millions of dollars in cloud cost savings annually
  • Participate in on-call rotation and collaborate with our operations team to triage and resolve production incidents with urgency and precision
  • Build observability and introspection tooling that gives engineers deep, real-time visibility into system health and bottlenecks
What You Should Have
  • U.S. Citizenship along with the ability to obtain a Top Secret Security Clearance. Please note that visa sponsorship is not available.
  • Genuine curiosity about how cloud infrastructure works — and a passion for sharing that knowledge with your team
  • Proven ability to analyze, optimize, and improve reliability in high-traffic, production internet applications
  • A strong mentoring instinct and commitment to engineering excellence: you lead by example in code reviews, testing, design docs, and debugging
  • Deep, hands-on AWS experience — broad familiarity across many services with deep expertise in at least a few
  • Demonstrated experience deploying cloud applications and managing infrastructure-as-code using Terraform and/or Cloud Formation
  • Strong ability to troubleshoot and debug complex issues across infrastructure, applications, and distributed systems
  • A track record of professional software development you're proud of — you can point to real-world systems you've built, scaled, and improved
  • Experience working with Kubernetes (K8s)
Qualifications
  • 7+ years of professional experience in cloud engineering or a closely related discipline, working in a collaborative team environment
  • Strong computer science fundamentals: data structures, algorithms, distributed systems, programming languages, and information retrieval
  • Bachelor's degree in Computer Science, Engineering, or a related field — or equivalent training, fellowship, or work experience
  • Proficiency in one or more functional or imperative programming languages — Python, Go, or PHP preferred
  • Hands-on experience with software engineering, scripting, automation, and orchestration tools (e.g., Bash, Chef, Jenkins, Terraform)
  • Extensive, production-grade experience provisioning, configuring, and maintaining AWS environments
  • Experience managing large-scale Kubernetes systems (EKS or Bare Metal)
Bonus Points
  • Deep expertise in core AWS services such as EKS, EC2, IAM, Fargate, S3, or Lambda
  • AWS Professional or Specialty certification(s)
  • Experience designing or operating large-scale, high-volume distributed systems
  • A proven history of driving significant cloud cost reductions at scale
  • Familiarity with observability tooling (e.g., Datadog, Prometheus, Open Telemetry) and SRE practices
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