Backend Engineer - AI Systems

About Act

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