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VAST Data in the United States is seeking a Senior Software Engineer to design, build, and optimize high-performance distributed systems, core data engines, and backend infrastructure.
You will work across storage, data path, and kernel layers, tackling petabyte-scale datasets, mastering C/C++ and Linux internals to deliver scalable, low-latency solutions for AI workloads.
Shape the Future of AI Infrastructure with VAST Data
This is a rare opportunity to join one of the fastest-growing infrastructure companies in tech history, right at the epicenter of the AI revolution.
Recognized by Forbes as "the future of the market," VAST Data is building the foundational enterprise software powering the AI era. We engineer platforms that capture, catalog, refine, and protect massive datasets across data centers, edge, and cloud, making real-time analytics, AI training, and inference simpler and faster than ever before.
Our explosive growth is fueled by relentless engineering innovation, a customer-first mindset, and a team of fearless VASTronauts who thrive on solving computing's hardest problems. Join us at this pivotal moment in technology history and make a lasting impact on how the world processes data.
We are seeking a talented and experienced Software Engineer to design, build, and optimize high-performance distributed systems, core data engines, and backend infrastructure. This role requires deep system-level architecture understanding, the ability to handle large-scale clusters processing petabytes of data, and mastery of modern C/C++ and Linux environment internals.
Storage Platform: Focuses on building a next-generation distributed storage platform handling petabytes of data across large clusters specifically designed to power AI, enterprise, and analytics workloads. Handling everything that touches the hardware and operating system aspects in a software defined storage system
Data Path: Focuses on engineering a highly distributed, latency-critical Hot I/O Data Path and Element Store engine. This role is responsible for the ingestion, state-of-the-art compression, encoding, and retrieval of multi-protocol data (files and objects) under massive concurrency and ultra-low latency requirements.
Database: Focuses deeply on core relational database internals, specifically designing low-level storage engines, B-Tree/LSM-Tree data structures, MVCC concurrency control, and query execution planners.
Kernel: Focuses on the lowest software layers, emphasizing Linux Kernel development and block-level storage/file system engineering.
Protocols: Focuses strictly on engineering high-concurrency data/metadata paths that replicate external AWS S3 object-storage behavior and correctness under heavy retry and failover pressure.
Cloud: Focuses on cloud-native storage deployment (VAST OS), adapting and scaling complex high-availability storage infrastructure across major hyper-scaler cloud environments (AWS, Azure, GCP).
Compute Kafka: Focuses on distributed event-streaming and messaging platforms, specifically building a high-scale, exactly-once broker compatible with the Apache Kafka wire protocol.
Qualifications & Requirements