Senior Software Engineer – Foundational Data Systems for AI

November 7

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Granica

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Artificial Intelligence • SaaS • Cybersecurity

Granica is a company that specializes in optimizing data for artificial intelligence applications. They offer a comprehensive AI data readiness platform designed to build and manage high quality data that powers safe, efficient, and effective AI at scale. Granica provides solutions like Crunch, which optimizes data storage and processing, Screen, which ensures data privacy and security, and Signal, which selects and refines data for AI training. They focus on reducing data storage and compute costs while enhancing AI development and data pipeline efficiency. Granica also emphasizes ethical AI governance, data encryption, and bias detection, catering to various industries such as financial services, e-commerce, and robotics.

11 - 50 employees

🤖 Artificial Intelligence

☁️ SaaS

🔒 Cybersecurity

📋 Description

• Global Metadata Substrate. Architect the transactional and metadata substrate that supports time-travel, schema evolution, and atomic consistency across petabyte-scale tabular datasets. • Adaptive Engines. Build systems that reorganize data autonomously, learning from access patterns and workloads to maintain peak efficiency without manual tuning. • Intelligent Data Layouts. Optimize bit-level organization (encoding, compression, layout) to extract maximal signal per byte read. • Autonomous Compute Pipelines. Develop distributed compute systems that scale predictively, adapt to dynamic load, and maintain reliability under failure. • Research to Production. Implement new algorithms in compression, representation, and optimization emerging from ongoing research. Opportunities to publish and open-source are encouraged. • Latency as Intelligence. Design for minimal time between question and insight, enabling models and humans to learn faster from data.

🎯 Requirements

• Depth in distributed systems: consensus, partitioning, replication, fault tolerance. • Experience with columnar formats such as Parquet or ORC and low-level encoding strategies. • Understanding of metadata-driven architectures and adaptive query planning. • Production experience with Spark, Flink, or custom distributed engines on cloud object storage. • Proficiency in Java, Rust, Go, or C++ with an emphasis on clarity and quality. • Curiosity about theory of the mathematics of compression, entropy, and learning efficiency. • A builder’s mindset: pragmatic, rigorous, and grounded in long-term systems thinking.

🏖️ Benefits

• Competitive salary, meaningful equity, and substantial bonus for top performers • Flexible time off plus comprehensive health coverage for you and your family • Support for research, publication, and deep technical exploration