Backend Engineer, AI Systems

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About ActAI There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal to no prompting.
Our first application is an agent-first mobile communication app. We believe building applications that users use daily for communication, coordination and collaboration needs will help integrate AI into their lives. The net effect is to eliminate misinformation, achieve low coordination costs, enable high quality tasks and collaboration at scale with minimal or little prompting.

Role Build and maintain backend services and APIs for AI-powered applications

Develop inference orchestration systems that connect LLMs, application services and external tools

Design APIs for streaming responses, asynchronous processing and real-time interactions

Improve system performance through caching, batching, concurrency and database optimisation

Implement monitoring, logging, alerting and error handling for production services

Diagnose and resolve production issues involving latency, service failures and high traffic

Work with ML, frontend and mobile engineers on API design, system integration and deployment

Requirements 3+ years of backend software engineering experience building production systems

Strong programming skills in Python, Node.js or similar backend technologies

Experience designing and maintaining REST or gRPC APIs, databases and distributed services

Understanding of asynchronous processing, concurrency, caching and message queues

Experience building scalable services and optimising latency, throughput and resource usage

Experience with SQL or NoSQL databases, Docker and cloud infrastructure

Ability to debug production issues using logs, metrics and distributed tracing

Nice to Have Experience integrating LLM APIs, inference services or AI-powered applications

Experience with model serving, streaming inference or orchestration frameworks

Experience with Kubernetes and container orchestration

Familiarity with PyTorch, vLLM or open-source model deployment

Experience building real-time communication, messaging or high-traffic

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