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Senior Software Engineer - Multi Cloud Efficiency

Build and own scalable backend infrastructure that optimizes cloud resource utilization and cost attribution across AWS, Azure, and Google Cloud. The role requires 6+ years of distributed-systems engineering experience and strong system-design, optimization, and technical leadership skills.

About the job

Responsibilities

  • Lead projects from concept through deployment, designing and building scalable systems that handle high-volume data streams for cost attribution and resource management.
  • Identify and eliminate inefficiencies in cloud architecture, reducing resource waste and improving attribution accuracy.
  • Own the full lifecycle of services, including code quality, monitoring, and operational overhead.
  • Collaborate with product and infrastructure teams to translate business needs into technical specifications.
  • Build tooling that simplifies cloud economics for engineers and budget owners.
  • Contribute to code reviews, share engineering best practices, and mentor junior engineers.
  • Integrate cloud efficiency checks into developer workflows.
  • Build automation and AI/agentic tooling to detect waste, attribute cost, and remediate issues.

Requirements

  • 6+ years of experience producing high-quality production code and detailed technical design documents for distributed systems.
  • Ability to break down complex, multi-month projects into actionable milestones and tasks.
  • Strong understanding of distributed-systems best practices, including monitoring, documentation, testing, and fit and finish.
  • Experience optimizing cloud resource utilization or developing large-scale distributed tools.
  • Ability to make well-reasoned trade-offs between system performance, development velocity, and technical debt.

Benefits

  • Comprehensive benefits and perks are offered, with details varying by region.

Skills

Distributed Systems, AWS, Microsoft Azure, GCP, Cloud Optimization, Cost Attribution, Resource Management, Monitoring, Testing, Technical Design, Automation, Artificial Intelligence, Data Streams, Infrastructure

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