AI / ML Architect

AI Infrastructure Architecture :

• Design and implement asynchronous multi-agent orchestration
• Own end-to-end latency from user message to AI response
• Build resilient inference pipelines that gracefully degrade under load
• Implement intelligent request routing and load balancing for AI workloads
• Migrate critical AI conversation flow from monolith to dedicated services
• Implement WebSocket / streaming infrastructure for real-time chat
• Design circuit breakers and fallback strategies for AI model failures
• Build comprehensive observability for AI system performance
• Optimize credit data retrieval and caching Requirements Experience :
• 6+ years building production systems handling >10k concurrent users
• Proven experience with async / event-driven architectures (not just REST APIs)
• Hands-on experience scaling ML / AI inference in production
• Deep understanding of caching strategies (Redis, in-memory, CDN)
• Experience with message queues and real-time communication Expertise :
• Built systems integrating multiple LLM / AI models in production
• Experience with AI model serving frameworks (TensorFlow Serving, Triton, etc.)
• Understanding of AI inference optimization (batching, caching, model quantization)
• Knowledge of conversation state management and context handling
• Has debugged production issues under high AI inference load

(ref : hirist.tech)