We are building a next-generation real-time data processing system powering large-scale, high-concurrency applications in the gaming and AI space.
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This role sits at the intersection of:
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You will design and build high-performance Python microservices that process massive streams of data with sub-second latency.
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What You’ll Do
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Design and build high-performance Python microservices for real-time data processing
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Develop and maintain streaming data pipelines using Kafka and stream-processing frameworks
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Architect and scale distributed systems handling high-throughput, low-latency workloads
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Optimize system performance, identify bottlenecks, and ensure reliability in production
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Work closely with Data, AI, and Platform teams to translate complex logic into scalable systems
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Build robust observability systems (monitoring, logging, tracing)
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Drive best practices in code quality, system design, and engineering standard
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What We’re Looking For\nMust-Have Requirements
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8–10+ years of software engineering experience
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Solid experience with real-time / streaming data processing
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Kafka (must)
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Flink / Kafka Streams / similar frameworks
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Strong experience with distributed systems and high-concurrency architectures
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Hands-on experience with
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MongoDB (production-level usage)
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Experience with
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Redis or other caching systems
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Strong system design and problem-solving skills
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Nice to Have
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Experience with
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FastAPI or similar frameworks
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Familiarity with
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AWS / cloud infrastructure
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Experience with
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Docker / Kubernetes
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Background in high-scale consumer (B2C) systems
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Experience in gaming, anti-cheat, or real-time decision systems
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Language
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Python
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Streaming
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Kafka, Flink / Kafka Streams
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Database
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MongoDB, Redis
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What Makes This Role Unique
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Work on real-time systems with sub-second latency requirements
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Solve data streaming challenges at scale
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High ownership: design systems end-to-end, not just components
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Direct impact on core platform performance and reliability
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Fully remote, general team
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Collaborate with engineers across regions and domains