# Principal Software Engineer, Cloud Product Engineering at Aerospike

- Company: Aerospike
- What the company does: Aerospike is the real-time database for mission-critical use cases and workloads, including machine learning, generative, and agentic AI. Backed by NEA.
- Company website: https://aerospike.com/
- Type: Startups
- Level: Principal and up
- Location: Mountain View, CA
- Work setup: On-site
- Pay: $260K to $320K base salary per year (USD)
- Posted: 2026-09-12
- Apply by: 2026-10-27
- Apply: https://ats.rippling.com/aerospike-inc/jobs/856e97df-23b1-471f-87fe-f19bbc06f966
- Page: https://www.1752.vc/careers/jobs/aerospike-principal-software-engineer-cloud-product-engineering/

## About the role

We are seeking a Principal Software Engineer to serve as a technical authority and strategic architect for our Cloud Engineering organization. In this role, you will define the architectural vision and drive the execution of our next-generation, global multi-cloud SaaS platform. Your work will fundamentally shape how global enterprises deploy, operate, and scale Aerospike at extreme velocity and petabyte scale—pushing the absolute limits of real-time, always-on distributed systems.

## What they're looking for

- 10+ years of hands-on experience designing, building, and operating large-scale distributed systems and cloud platforms
- Proven Track Record: Experience acting in a Principal, Staff+, or Lead Architect capacity for a high-growth SaaS, IaaS, or database platform
- Deep Distributed Systems Expertise: Mastery of fault tolerance, consensus protocols, multi-tenant isolation, data partitioning, and consistency models
- Cloud-Native Systems Mastery: Deep expertise in Go (preferred) or other statically typed languages (Java, C++, Rust), alongside advanced Kubernetes internals and custom controller/operator development
- Multi-Cloud Architecture: Deep production experience across major public clouds (AWS, GCP, Azure) at massive scale
- Data & Storage Systems: Deep conceptual and practical understanding of NoSQL internals, access patterns, storage engine mechanics, and high-throughput data pipelines

Tags: Engineering