Own initiatives end-to-end: clarify and extend requirements with stakeholders, propose what to build, and see it through release and operation
Move from idea to working prototype in days, then evolve prototypes into production systems that handle edge cases, scale, and adversarial conditions
Apply AI agentically across the full SDLC, and contribute back to our internal agentic ecosystem: the workflows and tools the rest of the team relies on
Define release readiness: test strategy, rollout plans, observability, runbooks, and treat security, maintainability, and documentation as first-class concerns
Design and integrate distributed systems where they matter: messaging (e.g. Kafka), orchestration (e.g. Kubernetes), performance-sensitive protocols (e.g. Aeron, gRPC, Protobuf), etc
Job Requirements
5+ years of professional software engineering, with a cle...
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