Backend Engineer, AI Systems

Role overview Build the backend foundation for AI-powered applications, including APIs and services that connect language models, product features and external tools. The work emphasizes responsive, reliable systems that support streaming and real-time interactions, while partnering with machine learning, web and mobile engineers on integration and deployment.

Responsibilities - Develop and maintain backend services and APIs for AI product features. - Build inference orchestration that connects models with application services and external tools. - Design APIs for streaming responses, asynchronous work and real-time use. - Improve performance through caching, batching, concurrency and database tuning. - Add monitoring, logs, alerts and error handling to production services. - Investigate service incidents involving latency, failures or high traffic, using operational data to identify causes. - Coordinate API design, integration and releases with machine learning, frontend and mobile teams.

Requirements - At least three years of backend engineering experience building production systems. - Strong skills in Python, Node.js or a comparable backend language. - Experience designing and maintaining REST or gRPC APIs, databases and distributed services. - Understanding of asynchronous processing, concurrency, caching and message queues. - Experience scaling services and improving latency, throughput and resource use. - Familiarity with SQL or NoSQL databases, Docker and cloud infrastructure. - Ability to troubleshoot production systems using logs, metrics and distributed tracing.

Nice to have - Experience integrating LLM APIs, inference services or AI applications. - Familiarity with model serving, streaming inference or orchestration frameworks. - Experience with Kubernetes, PyTorch, vLLM or open-source model deployment. - Experience building real-time communication, messaging or high-traffic systems.