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Rogo

Software Engineer: Platform

New York City$250k–$315kfulltimemidAdded today

About this role

Rogo seeks a Platform Engineer to architect and scale a Kubernetes-based infrastructure supporting enterprise AI applications in finance. You'll own platform reliability, developer experience, and infrastructure-as-product while enabling 10x customer growth at a well-funded fintech startup.

What you'll do

  • Design and implement scalable Kubernetes solutions for secure enterprise workloads with clear failure modes
  • Define reliability initiatives including SLOs, capacity planning, and resilience improvements
  • Build and maintain internal platform systems: deployments, environments, and developer tooling
  • Identify and resolve system misconfigurations and architectural risks at scale
  • Create self-serve tooling and guardrails that multiply product engineer effectiveness
  • Establish engineering standards and design principles for complex infrastructure problems

What they're looking for

  • Kubernetes (production-grade, scaling from early-stage to critical workloads)
  • Distributed systems design and tradeoffs
  • Infrastructure-as-code and deployment automation
  • Observability and monitoring systems
  • Systems thinking and architectural design
  • Single-tenant architecture (bonus)
  • Financial services or regulated environment experience (bonus)
  • Banking security and data governance (bonus)

Benefits

  • Work on ambitious, technically demanding problems in AI and finance
  • Join a high-talent-density team at a well-funded, fast-growing startup
  • Significant technical ownership with company-wide impact
  • Opportunity to shape platform direction during critical scaling phase
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Rogo

Rogo builds a financial AI platform with a focus on data-driven insights and user experience. The company is hiring Analytics Engineers to develop data pipelines and reporting tools, and Design Engineers to enhance its design system and user interactions.

View all jobs at Rogo

Likely interview questions

  • Describe your experience scaling Kubernetes infrastructure from early-stage to production-critical workloads—what were the biggest bottlenecks?
  • Walk us through a time you identified and resolved a major architectural risk or misconfiguration in a distributed system.
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