Principal Sofware Engineer, Applied AI

Pure Storage•Santa Clara, CA

15h•$203,000 - $275,000•Onsite

About The Position

As the Principal Software Engineer, Applied AI, you will guide the platform from pre-release into production-ready customer deployments and establish the engineering standards needed to scale. This is an individual-contributor leadership role: you will set technical direction, influence product and architecture decisions, and remain hands-on with code, systems, and hardware. You will work with engineering leadership, a senior core team, product management, and early design-partner customers, leading through technical rigor, ownership, and pragmatic execution. The role includes setting technical roadmaps and release scope; designing the platform runtime, workload isolation boundaries, and public APIs; leading threat modeling and security-audit preparation; and writing and reviewing code. You will guide AI coding workflows, debug low-level systems, and verify workload behavior on real hardware and customer-like setups. You will mentor senior engineers, build resilient engineering and release practices, collaborate with early design partners, and define production readiness for dependable installation, upgrades, rollbacks, backups, and disaster recovery in customer environments. The position is primarily in-office at the Santa Clara, California office, subject to company policies and approved leave or work travel. The annual base salary range is $203,000–$275,000 USD; the role may also be eligible for incentive pay and/or equity.

Requirements

Proven track record leading the architecture and delivery of mission-critical infrastructure, runtime, or security software operating in production.
Recent experience writing production code, debugging distributed systems, and managing reliability through incident response and post-mortems.
Deep mastery in at least two of the following areas: container runtimes and isolation, workload identity/security, Kubernetes, distributed systems, or enterprise storage.
Experience using AI coding tools with a disciplined approach to automated testing, fuzzing, and manual verification of generated code.
Ability to pragmatically navigate and evolve existing codebases.
Strong communication skills to align engineers, product managers, and customers.

Responsibilities

Establish the technical roadmap and release scope, translating customer needs into priorities and making trade-offs about what to build, defer, or cut.
Design the platform runtime, workload isolation boundaries, and public APIs.
Lead threat modeling and preparation for security assessments and audits.
Write and review code, direct AI coding workflows, debug low-level systems, and verify workload behavior on real hardware and customer-like setups.
Mentor senior engineers and establish resilient engineering and release practices.
Work directly with early design partners to support a successful first launch.
Define production readiness and ensure dependable installation, upgrades, rollbacks, backup, and disaster recovery in customer environments.