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Bengaluru metro, visible backend role, and VC-backed brand yield moderate applicant competition.
Deep distributed-systems and real-time ML inferencing requirements make industry transfers difficult.
Explicit 8+ years and mandatory distributed-systems, real-time, and database expertise enforce strict filters.
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Develop and maintain highly available, secure authentication and API services with a focus on scalability and reliability.
Architect and operate real-time, auto-scaling data infrastructure and AI services for low latency, real-time inferencing of sensitive data.
Create observability solutions at scale and maintain documentation for both internal and public-facing services.
Expertise in one or more high-level programming languages like Go, Java, Python, or C++.
8+ years of experience with proven technical leadership in building scalable, distributed architectures and systems processing substantial data volumes or supporting millions of users.
Experience with scalable (thousands of RPS) and reliable (99.9% uptime) system design and production-quality deployment, monitoring, and reliability.
Experience with large-scale distributed storage and databases (e.g., Postgres, Cassandra) and data processing pipelines (Kafka, Flink, Snowflake, Databricks).
Strong background in building and operating low latency, real-time microservices particularly in AI or ML inferencing at scale.
Demonstrated ability to decompose complex business problems and lead teams to develop robust, scalable backend systems.
Experience working with agentic AI systems or real-time ML inferencing to optimize AI services for production environments.