Product Engineer, Platform
Confirmed on the employer's own hiring board on Sep 25, 2026. First seen by Alion on Sep 24, 2026.
About Archetype AI
At Archetype AI, we’re building the world’s first physical AI platform to bring artificial intelligence into the real world. Our foundation model, Newton, understands the physical world through objective sensor data and generates real-time insights into complex physical behaviors, from industrial machinery and systems to wearable devices and smart environments.
Formed by a high-caliber team from Google and backed by one of Silicon Valley’s most renowned venture funds, Archetype AI is in a Series A phase and rapidly advancing its technology for the next big leap. This is a unique opportunity to join an exciting, fast-growing AI team based in the heart of Silicon Valley.
Role Overview
We are seeking a talented Backend Engineer to architect, build, and scale foundational platform domains - ranging from public APIs/SDKs and agent execution runtimes to multi-tenant ingestion paths and orchestration engines for high-performance GPU jobs. You will translate frontier AI capabilities into resilient production infrastructure. Mid-level candidates will take end-to-end ownership of core backend services and user-facing capabilities. Senior candidates will drive technical architecture, establish system design patterns, and elevate engineering standards across the entire organization.
What You'll Own
Own backend product capabilities end to end: design, build, ship, operate, iterate. REST/Python APIs, agent runtimes.
Make research usable. Turn a new Newton capability into a versioned, observable, multi-tenant production path.
Build for more than one deployment model: our cloud, a customer VPC, on-prem, and increasingly the edge.
Treat developers as customers. API shape, error messages, SDKs, and internal tools should make the next team faster.
Operate what you build: SLOs, tracing, metrics, logs, on-call. Debug across code, datastores, queues, and Kubernetes.
Key Qualifications
4-8+ years of professional engineering with a backend, distributed systems, or developer-platform track record.
Strong production experience in Rust, Python, Go, or C++. Rust strongly preferred; be ready to work in it daily.
Have designed, built, and operated production services in the cloud (AWS, GCP, Azure) with Kubernetes and CI/CD.
Distributed systems in practice: concurrency, consistency, backpressure, retries, idempotency, 10× load.
Product judgment: has shipped APIs or infrastructure other engineers chose to use, and cares about the contract.
AI-assisted development is part of your workflow: coding agents daily, without lowering the quality bar.
Nice to Have
ML platform experience: model serving, GPU job scheduling, experiment tracking, or feature/data pipelines.
On-prem, hybrid, or customer-VPC deployments; multi-tenant SaaS; identity, keys, and audit.
Industrial or IoT protocols (MQTT, OPC-UA, Modbus, RTSP) or streaming media/sensor pipelines.
Prior time at an API, infrastructure, or AI-platform company where reliability was the product.