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Mid-level generalist backend role in metro at a recognizable startup attracts many qualified applicants.
Core backend and distributed-systems skills transfer well, but fraud/detection domain experience raises specialization sensitivity.
Explicit 5+ years, mandatory backend languages, cloud/microservices and daily AI tooling requirement create strict filters.
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End-to-end ownership of complex fraud and abuse detection features from requirements to production rollout.
Develop and maintain high-throughput, low-latency distributed backend services processing multi-dimensional signals at global scale.
Collaborate cross-functionally with SRE, product, and engineering teams; contribute to architecture, automated testing strategies, mentoring, and hiring.
5+ years experience building production backend services using Go, Python, Node.js, or Java (4+ years if holding a Master’s degree).
Daily hands-on use of AI coding tools (e.g., GitHub Copilot, Claude Code) integrated into development workflow.
Experience with cloud-hosted microservices and distributed systems at scale.
Strong knowledge of databases (relational and NoSQL), HTTP fundamentals, and automated testing practices.
Experienced backend engineer comfortable handling ambiguous problems to build reliable, scalable systems with real adversaries.
Familiar with agile development methodologies and cross-team collaboration in technical and architectural decisions.
Demonstrates leadership by mentoring engineers and improving team technical standards; actively involved in technical hiring.