Senior AI Software Engineer

The RoleWe’re building the next generation of real-time conversational AI systems. Our agents operate under real production traffic, where latency, scalability, reliability, and engineering quality are critical. We’re looking for a Senior AI Software Engineer to design and build the production systems that allow these agents to respond intelligently and reliably in real time. This is not an R&D or research role. This role sits at the intersection of AI engineering, backend systems, and distributed real-time architecture. You will take ownership of complex production systems behind our AI agents, including low-latency backend services, event-driven pipelines, agent orchestration, and the infrastructure patterns required to operate them at scale. We also believe that modern software engineering is changing. The strongest engineers are no longer measured only by how much code they write manually, but by how effectively they can design systems, orchestrate AI coding agents, and validate AI-generated work without compromising quality. What You’ll Do • Design, build, and operate production-grade backend systems powering our conversational AI platform. • Build low-latency, high-throughput services using Python, FastAPI, and asynchronous programming. • Develop real-time, event-driven systems using WebSockets, streaming technologies, queues, and parallel processing. • Design distributed architectures that remain reliable and responsive under significant production traffic. • Build and improve AI agent orchestration systems and LLM-powered applications. • Integrate LLM APIs, AI frameworks, communication infrastructure, and external AI providers into the platform. • Use technologies such as Redis and caching layers to improve latency, throughput, and system efficiency. • Profile production systems, identify performance bottlenecks, and optimise critical execution paths. • Improve system resilience, fault tolerance, observability, and production debugging capabilities. • Write comprehensive unit, integration, and load tests. • Design clean, modular, and maintainable architectures that can evolve as the product scales. • Work closely with AI, product, and engineering teams to translate agent capabilities into reliable production systems. • Use AI coding tools to accelerate development, debugging, testing, refactoring, and technical exploration. • Review and validate AI-generated code for architectural flaws, hallucinations, security issues, and maintainability risks. • Write a significant amount of production code while improving the overall engineering quality of the platform.