Senior Software Engineer

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.

Key Responsibilities

• Design & Develop Core Components: Build, maintain, and optimize highly scalable, resilient distributed services, storage engines, or data-processing pipelines written in C/C++.
• System Architecture & Resilience: Drive architectural discussions and implementations around high availability, data consistency, replication mechanisms, fault tolerance, and multi-node concurrency.
• Performance Optimization: Optimize hot execution paths, low-level data structures, memory management, and I/O subsystems to guarantee high throughput and minimal latency.
• Complex Debugging & Troubleshooting: Investigate and resolve intricate production issues spanning the application layer, distributed networking protocols, file systems, and operating system kernels.
• End-to-End Ownership: Take full technical ownership of critical features—from ambiguous requirements and system design through implementation, rollout, and observability in production environments.

Teams

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.

Requirements

Qualifications & Requirements

• Education: B.Sc. or M.Sc. in Computer Science, Software Engineering, Computer/Electrical Engineering, or equivalent practical experience.
• C/C++ Expertise: Strong hands-on experience in C/C++ systems programming, including design, coding, integration, and advanced debugging in production environments.
• Deep Linux Internals: Solid understanding of Linux operating systems, including process and thread management, synchronization primitives, memory allocation, and I/O performance troubleshooting.
• Distributed Systems: Proven track record of developing complex backend services or distributed platforms focusing on scalability, concurrency, reliability, and failover mechanisms.
• Networking Fundamentals: Strong working knowledge of networking concepts, including the OSI model, TCP/IP, routing, and distributed communication patterns.