Principal Sofware Engineer, Applied AI

Everpure•Santa Clara, CA

1d•$293,000 - $304,000•Onsite

About The Position

As Principal Software Engineer, Applied AI, you will guide Everpure’s platform from pre-release into production-ready customer deployments and establish engineering standards for scaling it. This individual-contributor leadership role involves setting technical direction, driving product and architecture decisions, and remaining hands-on with code, systems, and hardware. You will work directly with engineering leadership, a senior core team, product management, and early design-partner customers, leading through technical rigor, ownership, and pragmatic execution. You will establish the technical roadmap and release scope, translating customer needs into priorities and making trade-offs about what to build, defer, or cut. You will design the platform runtime, workload isolation boundaries, and public APIs, and lead threat modeling and audit preparation for security assessments. The role also includes writing and reviewing code, guiding AI coding workflows, debugging low-level systems, verifying workloads on real hardware and customer-like setups, mentoring senior engineers, and working with design partners toward a successful first launch. You will define production readiness and ensure dependable installation, upgrades, rollbacks, backup, and disaster recovery in customer environments. The position is based in Everpure’s Santa Clara, California office. The company describes its work environment as primarily in-office, with attendance subject to company policies and exceptions for PTO, work travel, or other approved leave.

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 audit preparation for security assessments.
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.