# Staff Software Engineer – Foundational Data Systems for AI

**Company:** [Granica](https://hotfix.jobs/companies/granica)
**Location:** San Francisco, CA
**Role:** Data Engineering
**Salary:** $240k – $290k/yr
**Experience:** 8+ years
**Skills:** Distributed Systems, Java, Rust, Go, C++, Spark, Flink, Columnar Formats, Consensus Algorithms, Data Compression
**Posted:** 2025-11-07

> Lead architecture of exabyte-scale distributed data systems that self-optimize via compression, metadata, and intelligent layouts to power efficient AI infrastructure. Requires deep expertise in distributed systems, low-level data representation, and leadership of large-scale production systems.

## Job Description

## What You’ll Build
- **Global Metadata Substrate**: Define and evolve the global metadata and transactional substrate that powers atomic consistency and schema evolution across exabyte-scale data systems.
- **Adaptive Engines**: Architect self-optimizing systems that continuously reorganize and compress data based on access patterns, achieving order-of-magnitude efficiency gains.
- **Intelligent Data Layouts**: Pioneer new approaches to encoding and layout that push theoretical limits of signal per byte read.
- **Autonomous Compute Pipelines**: Lead development of distributed compute platforms that scale predictively and maintain reliability under extreme load and failure conditions.
- **Research to Production**: Collaborate with Granica Research to translate advances in compression and probabilistic modeling into production-grade, industry-defining systems.
- **Latency as Intelligence**: Drive system-wide initiatives to minimize latency from insight to decision, enabling faster model learning and data-driven reasoning.

## What You Bring
- Mastery of distributed systems: consensus, replication, consistency, and performance at scale.
- Proven track record of architecting and delivering large-scale data or compute systems with measurable 10× impact.
- Expertise with columnar formats and low-level data representation techniques.
- Deep production experience with Spark, Flink, or next-generation compute frameworks.
- Fluency in Java, Rust, Go, or C++, emphasizing simplicity, performance, and maintainability.
- Demonstrated leadership—mentoring senior engineers, influencing architecture, and scaling technical excellence.
- Systems intuition rooted in theory: compression, entropy, and information efficiency.

## Bonus
- Familiarity with Iceberg, Delta Lake, or Hudi.
- Published or open-source contributions in distributed systems, compression, or data representation.
- Passion for bridging research and production to define the next frontier of efficient AI infrastructure.

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