Senior Software Engineer (Distributed Systems)

TL;DR

Senior Software Engineer (Distributed Systems): Designing and implementing highly scalable, distributed backend services for the metadata layer of the AI Data Cloud with an accent on high-throughput storage and retrieval systems. Focus on solving complex database engine problems, ensuring correctness at exabyte scale, and building APIs for internal and external consumption.

Location: Hybrid (Bellevue, WA, US)

Salary: $200,000 – $287,500

Company

A cloud-native AI Data Cloud platform powering the agentic enterprise through scalable metadata and data management.

What you will do

• Build core metadata storage and retrieval systems for catalog, lineage, and governance products.
• Develop high-throughput, low-latency distributed services in a cloud-native environment.
• Create APIs and frameworks for internal teams and external customers.
• Implement observability, reliability, and operational tooling for production metadata services.
• Design scalable data models that evolve with the platform's growing feature surface.

Requirements

• 7+ years of experience in backend software engineering.
• Strong proficiency in Java, C++, Go, or similar systems-level languages.
• Experience designing and operating distributed systems at scale (high availability, fault tolerance, consistency tradeoffs).
• Solid understanding of database internals, metadata management, or catalog systems.
• Proven ability to lead technical design and drive features end-to-end.
• Must be based in or able to work hybrid in Bellevue, WA, US.

Nice to have

• Experience with data catalog, data governance, or schema registry systems.
• Familiarity with cloud infrastructure on AWS, Azure, or GCP.
• Prior work on multi-tenant SaaS platforms.
• Contributions to open-source projects in the metadata or data infrastructure space.

Culture & Benefits

• Dynamic and fast-moving environment with an experimental mindset.
• Opportunity to help redefine the future of work within the agentic enterprise era.
• Culture of ownership, taking problems from ambiguity to production.
• Focus on technical mentorship and raising the engineering bar across the team.