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# Staff Platform Software Engineer, AI Enablement

- **Company:** Zipline
- **Location:** South San Francisco, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Audit Trail, Data Systems, Distributed Systems, Middleware, Fault Tolerance, Protocol Buffers, Reliability Engineering, Cloud Services, Service-Oriented Architecture, Software Engineering, System Software, Software Security, Rate Limiting, Event Driven Architecture, Apache Kafka, Operational Systems, Api Design, Api Gateway, Golang
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_dc256b425deebfa23560e346beb299c3

## About the Role

* 8+ years of software engineering experience, including experience building and operating production applications at meaningful scale.
 * Deep experience designing developer-facing APIs and distributed systems.
 * Strong application engineering judgment, with a track record of translating product, customer, or operational needs into maintainable production software.
 * Experience building cloud services and event-driven systems, including technologies such as Go, Protobuf, Kafka, and API-based service architectures.
 * Experience designing for reliability, scale, and safe handling of high-volume or unpredictable traffic.
 * Strong understanding of authentication, authorization, rate limiting, observability, and operational safety in production applications.
 * A collaborative, pragmatic approach to technical leadership: you set a high bar for production readiness while helping teams make progress.
 * Comfort using AI-assisted development tools as part of your engineering practice, along with the judgment to validate, harden, and operate the resulting systems., * Experience designing abuse-resistant or public-facing APIs.
 * Experience with platform engineering, API gateways, service meshes, or developer platforms.
 * Background in security engineering, application security, site reliability engineering, or incident response.
 * Experience establishing technical standards or governance in a fast-moving engineering organization.
 * Experience working with internal tools, data systems, or AI-enabled applications.
 * Experience building systems that support real-world operations, logistics, autonomous systems, or other high-reliability services.

## Description

* Define and build the "paved road" for connecting AI-enabled applications and internal tools to production systems, including services that support delivery operations and customer experience.
 * Design and implement reusable APIs, gateways, middleware, and integration patterns that are scalable, secure, observable, and straightforward for engineers to adopt.
 * Partner early with Forward Deployed AI Engineers on high-impact projects, helping them select production-ready integration patterns and move successful prototypes into supported services.
 * Own the technical decision for integrations that access protected production boundaries: approve the proposed design, require a safer redesign, or decline an integration that cannot meet Zipline's standards for operational safety and reliability.
 * Define and operate the platform safeguards that protect production systems-including authentication, authorization, workload isolation, rate limiting, auditability, capacity management, observability, alerting, graceful degradation, and safe failure modes.
 * Establish clear technical standards and governance for how AI-enabled tools access production and operationally critical systems.
 * Create reference implementations, documentation, and developer experiences that make the secure, supported path the easiest path to adopt.
 * Partner with service-owning teams to ensure platform components and integrations have explicit ownership, operational expectations, and sustainable support models.

What Success Looks Like

 * Teams building AI-enabled tools use well-defined, self-service integration patterns instead of creating one-off production connections.
 * New applications can reach the production systems they need without weakening reliability, security, or the operational systems supporting Zipline's delivery service.
 * The platform is broadly adopted by Forward Deployed AI Engineers and application teams because it is practical, well-documented, and materially speeds up safe delivery.
 * Production integrations have explicit service ownership, observability, capacity expectations, and safe operating boundaries.
 * Integration risks are identified and resolved before they affect customers, delivery operations, or critical services.