Build and operate backend systems that serve AI-powered features in production.

Design inference pipelines, orchestration layers, and service boundaries around models.

Own production concerns: monitoring, logging, alerting, and incident response.

Optimize latency and throughput across inference, caching, batching, and streaming.

Ideal Experiences

Strong backend engineering fundamentals in production environments.

Experience running high-throughput, low-latency services.

Familiarity with AI inference patterns (LLMs, embeddings, multimodal).

Comfortable debugging distributed systems under load.

Bias toward shipping and learning from production behavior.

Backend systems run reliably at scale, handling production AI traffic with low latency and high throughput.

APIs are stable, clear, and support seamless integration with frontend and ML systems.

Backend Engineer, AI Internal Systems

Responsibilities