Backend AI Engineer, Brain Technologies

• Strong programming skills in one or more languages (Node.js, Go, Python preferred)
• Experience designing distributed backend systems and scalable APIs
• Proficiency with relational and non-relational databases (Postgres, MySQL, MongoDB, Redis, vector databases a plus)
• Experience with containerized infrastructure (Docker, Kubernetes, GKE)
• Experience with IaC tooling (Terraform, Ansible) and cloud platforms (GCP or AWS)
• Familiarity with LLM-powered systems or interest in learning quickly (OpenAI APIs, RAG patterns, prompt pipelines, real-time AI services)
• A systems thinker who enjoys operating across backend, infra, and AI workflows
• Someone who learns rapidly and thrives in ambiguity
• A collaborator who communicates clearly and cares about product impact
• A builder excited to help launch one of the world’s first AI-native phones
• You love solving problems, owning outcomes, and enabling teammates to succeed

Desirable

• As a Backend Engineer with DevOps responsibilities, you will design and operate the core services that power our AI platform — including agent orchestration, personalization, real-time API pipelines, and the backend systems that support our upcoming global device launch
• This is a hands-on, high-ownership role where you will influence system architecture, scale production workloads, automate infrastructure, and evolve a unified backend supporting both mobile devices and cloud-based AI services. You’ll work closely with ML, mobile, and systems engineers to bring generative AI into everyday user experiences
• Architect and implement scalable backend services that process high-volume, latency-sensitive AI inference and user-intent traffic (real-time or near-real-time request paths)
• Design and maintain APIs used by Natural OS, the AI Phone, and cloud AI orchestration systems
• Work with distributed systems, streaming pipelines, vector stores, and event-driven architectures
• Integrate LLM-powered features safely and efficiently (rate-limiting, prompt-pipeline design, real-time personalization, caching)
• Ensure backend reliability through automated testing, observability, and performance tuning
• Own cloud infrastructure used for device-to-cloud communication, LLM routing, metrics, and model-runtime services
• Implement and maintain Infrastructure-as-Code (Terraform, Ansible, Docker/K8s, GKE/GCP)
• Build CI/CD pipelines for backend and mobile releases, ensuring fast and safe iteration cycles
• Drive system observability (logging, metrics, tracing) across both backend and device fleets
• Improve security practices, secrets management, and compliance standards in a multi-region environment
• Participate in on-call rotations, incident response, and post-mortems for critical systems
• Work closely with AI/ML engineers on model integration, inference load balancing, and data-flow design
• Collaborate with mobile OS engineers to design reliable protocols for AI-driven interactions between device and cloud
• Influence long-term platform architecture and take ownership of key capabilities as we scale