Rogo
Software Engineer: Platform
- Confirmed live in the last 24 hours
- $250k–$315k
- Mid level
- Full-time
- On-site · New York City
- Added 1 month ago
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.
- Industry
- Technology & Software
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.