[Hiring] Principal AI Cloud Storage Engineer @Blaze Talent

Role Description

We're looking for a Principal Software Engineer to define and build Neo Cloud's AI cloud storage platform. This is a senior individual-contributor role for an experienced system architect who can operate at the intersection of customer needs, system architecture, and production operations — translating what AI/ML customers will need in the future, into a storage system that is performant, resilient, and economical at massive scale.

Key Responsibilities

• Identifying customer requirements:
  • Engage directly with customers, solutions architects, and product teams to understand future storage requirements for AI/ML workloads.
  • Extrapolate from current usage patterns and industry trends to anticipate future requirements.
  • Partner with product management to prioritize platform investments based on near-term customer needs and longer-term strategic bets.
• System design, implementation, and operations:
  • Design, implement, and operate AI cloud object and file storage systems, including the data path, metadata path, and control plane.
  • Take a system-level approach that accounts for the full characteristics of AI workloads, building end-to-end solutions.
  • Architect for the specific demands of AI workloads: very high aggregate throughput, support for massive numbers of small and large objects and files, efficient checkpointing at scale, and predictable tail latency under heavy concurrent load.
  • Drive core storage system design decisions, including durability and consistency models, erasure coding and replication strategies, metadata scalability, multi-tenancy and isolation, and S3-compatible and POSIX/file-protocol API design.
  • Take end-to-end ownership of services in production: build for observability and operability from day one, participate in on-call, lead incident response and root-cause analysis for critical issues, and drive long-term reliability and performance improvements.
  • Identify and eliminate performance bottlenecks and scalability limits before they become customer-facing problems; lead capacity planning for rapid growth.
  • Deep understanding of data privacy and security and its implication on performance.
  • Ability to partner with network engineers to deliver complete AI storage system.
• Technical leadership:
  • Strong bias to action and resolution of technical decisions.
  • Set technical direction and best practices for the storage organization; author and review design documents for significant architectural changes.
  • Provide deep technical mentorship to senior and staff engineers; raise the engineering bar across the team through code review, design review, and hands-on collaboration.
  • Influence technical strategy across adjacent teams.

Qualifications

• 10+ years of professional software engineering experience building and operating cloud storage systems in production.
• Direct experience with AI-focused storage platforms such as DDN, Weka, or VAST, including their architectural approaches to throughput, caching, and GPU-cluster integration.
• Deep understanding of distributed systems fundamentals: consistency models, replication, consensus, partitioning, failure detection, and recovery.
• Proven experience operating high-scale distributed systems in production, including on-call ownership, incident response, and driving systemic reliability improvements.
• Strong systems programming skills (e.g., Go, C++, Rust, or Java) and comfort working across the stack from low-level I/O and networking to distributed control planes.
• Excellent written and verbal communication skills.

Nice to have

• Experience designing or tuning local node caching layers to accelerate AI training and inference data access.
• Experience with high-performance networking.
• Contributions to open-source storage projects, relevant patents, or published technical papers/talks.