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services.\nImplement WebSocket/streaming infrastructure for real-time chat.\nDesign circuit breakers and fallback strategies for AI model failures.\nBuild comprehensive observability for AI system performance, latency, error rates, and fallback triggers.\nOptimise credit data retrieval and caching strategies feeding into AI conversations.\nRequirements:\n3-5 years building production systems handling > 10k concurrent users.\nProven experience with async/event-driven architectures (not just REST APIs).\nHands-on experience scaling AI inference calls in production, routing, batching client-side, and retries.\nDeep understanding of caching strategies (Redis, in-memory, CDN).\nExperience with message queues and real-time communication protocols (WebSocket, SSE, Kafka or similar).\nAI-Specific Expertise:\nBuilt systems integrating multiple LLM/AI models or providers in production, with fallback between them.\nExperience working against AI model serving endpoints (TensorFlow Serving, Triton, vLLM, or hosted LLM APIs).\nUnderstanding of inference optimisation from the application side: batching, response caching, prompt/context size management.\nKnowledge of conversation state management and context handling across multi-turn, multi-agent flows.\nHas debugged production issues under high AI inference load.","description_format":"text","description_chars":1702,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Personal Finance Apps & Education"],"lifecycle":[{"event":"open","at":"2026-10-12T12:15:51Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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