Senior Distributed Compute Engineer - Spark & AI Infra

Agilesoft; San Francisco (CA); On-site; USD 160,000 - 240,000; Full time

Benefits offered by this job

Equity

Health coverage

401(k) with company match

Unlimited PTO

Daily catered meals

Job summary

Granica in Mountain View, CA is hiring a Senior Software Engineer to build distributed compute systems for enterprise-scale data and AI workloads. You will work on core infrastructure behind Crunch, Granica's optimization product, including systems for distributed execution, workload scheduling, and compute cost reduction.

You will own systems involving Apache Spark, Spark SQL, Trino, Presto, Flink, and lakehouse formats like Iceberg, Delta Lake, and Hudi, aiming to improve performance and

Qualifications

• Strong engineering depth in distributed systems and data processing.
• Production experience with distributed compute or query systems such as Spark, Trino, Presto, Flink, Databricks, EMR, Glue, Hive or similar.
• Hands-on experience improving performance, reliability, or cost efficiency for large-scale data-processing workloads.

Responsibilities

• Build distributed compute systems for large-scale analytical and AI workloads.
• Improve performance and cost efficiency across Spark, Trino, Presto, Flink and Snowflake-adjacent environments.
• Design workload-aware systems for query execution, resource allocation, and scheduling.

Skills

Distributed systems

Spark internals

Query engines

Performance optimization

Go/Rust/C++

Cloud infrastructure

Tools

Apache Spark

Trino/Presto

Flink

Iceberg/Delta Lake/Hudi

Parquet/ORC

Job description

Granica in Mountain View, CA is hiring a Senior Software Engineer to build distributed compute systems for enterprise-scale data and AI workloads. You will work on core infrastructure behind Crunch, Granica's optimization product, including systems for distributed execution, workload scheduling, and compute cost reduction.

You will own systems involving Apache Spark, Spark SQL, Trino, Presto, Flink, and lakehouse formats like Iceberg, Delta Lake, and Hudi, aiming to improve performance and