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Niche HPC/distributed database expertise and seniority sharply reduce candidate pool despite Bangalore location.
Highly specialized systems, HPC, and database-internals skills limit cross-industry transferability.
Explicit 8+ years and mandatory low-level C++, MPI, RDMA, SIMD, and database-internals requirements.
Own design and development of next-gen massively parallel processing (MPP) distributed database engine handling real-time queries on very large retail and consumer analytics datasets.
Drive architecture and implementation of high-performance, low-latency C++ backend focused on hardware-optimized software, SIMD vectorization, MPI/OpenMP parallelism, and distributed systems protocols.
Lead innovation of native in-database machine learning and vector search capabilities integrated into the MPP engine to enable zero-copy, high throughput analytics and ML inference.
Bachelor's degree in Computer Science Engineering or related field (Masters preferred for this senior level).
8+ years hands-on production experience with modern C++ (C++17/20/23), including template metaprogramming and memory allocator expertise.
Expertise in HPC and distributed systems: MPI, OpenMP, MapReduce, plus SIMD intrinsics optimization and concurrency mechanisms.
Practical experience with core database internals such as query operators, storage engines, transaction managers, and performance tuning.
Senior-level engineer with strong cross-domain expertise bridging HPC, Big Data distributed systems, and low-latency machine learning infrastructure.
Experienced in developing scalable, hardware-aware distributed database kernels running on multi-node clusters with deep understanding of CPU architecture and network fabrics.
Comfortable operating in a multi-timezone, elite engineering team environment involving architecture leadership and rigorous peer review.