Staff AI-Native Software Engineer

Staff AI-Native Software Engineer

Cricut® empowers people to make and personalize almost anything—from custom cards and apparel to everyday items and home décor. Our smart cutting machines, design apps, and materials make creativity easy and accessible for everyone. We believe everyone is born creative, and our mission is to put the power of handmade into the hands of all. With a passionate community of Makers around the world, Cricut helps turn inspiration into real, tangible creations—one project at a time.

Let's make.

We're looking for a Staff AI-Native Software Engineer to architect the future of a cross-platform design product—spanning desktop and mobile apps for manual and AI-assisted design creation, cloud-saved projects, and rock-solid connectivity and execution on cutting machines over Bluetooth, USB, and Wi-Fi.

This role demands deep systems thinking across client apps, backend services, device connectivity, and hardware/firmware integration, with a mandate to make the entire stack secure, scalable, extensible, maintainable, observable, and genuinely delightful to use. Just as important, you'll shape how AI gets woven into both the product experience itself and the way our engineering organization builds software.

Key Responsibilities

• Champion AI-native engineering practices (agentic coding, AI-assisted review, test generation, AI-augmented design/ADRs) while staying hands-on in critical code paths and maintaining quality, security, and human oversight.
• Drive end-to-end architecture across app, cloud, and device layers—data/control flow, latency, reliability, failure recovery, APIs/integration contracts (with versioning), cross-platform app design, and reliable Bluetooth/USB/Wi-Fi connectivity.
• Lead architecture governance up front for major initiatives: author/review ADRs, run architecture reviews, and keep major PRs traceable to their ADR.
• Own planning, estimation, and delivery accountability—scrutinizing estimates and separating engineering effort from calendar time.
• Ensure reliability, security, and performance through retries, secure auth, encryption, certificate validation, and permissions.
• Partner cross-functionally with product, design, QA, manufacturing, firmware/EE, AI/ML, support, and security, and mentor engineering leaders on performance/UX/reliability/cost tradeoffs.
• Own safe shipping and release health—feature flags, progressive rollout, kill-switches, A/B experiments, and telemetry-driven tracking of crash-free rate, performance budgets, and defect counts.

• 8+ years shipping production software across the full stack—client apps, backend services, and device integration—with strong proficiency in several of the following technologies:
  Swift, Kotlin, JavaScript/Type Script, C#, React, and Python.
• At least a year of hands-on, pragmatic use of modern AI engineering tools (Claude Code, Cursor, Copilot, agentic SDKs), with the credibility to lead a team in adopting them safely—paired with production experience integrating AI/LLM capabilities: model orchestration, retrieval, agentic patterns, evals, and managing latency/cost/reliability tradeoffs.
• Proven track record building cross-platform products at scale across iOS, Android, desktop, and web, using shared code, platform abstraction layers, and disciplined API contracts;
  React Native or Flutter experience a plus.
• Strong expertise in device connectivity—Bluetooth, Wi-Fi, and USB—including BLE GATT design, Wi-Fi provisioning, and mDNS/SSDP discovery, plus the real-world grit of pairing, interference, bandwidth, reconnection, and platform constraints.
• Working knowledge of embedded and hardware integration: firmware constraints, command protocols, calibration, safety, OTA updates, and error codes/telemetry.
• Strong backend experience with REST APIs, microservices, and backend integration, plus a solid security foundation including hands-on asymmetric cryptography.
• A track record leading large-scale refactors and modernization efforts, with the ability to communicate architecture clearly—diagrams, ADRs, tradeoffs—and influence across teams.
• Comfortable operating at roughly 90% hands-on implementation, 10%…