AI Engineering Architect

Educational Requirements ; Bachelor of Engineering Service Line ; Infosys Quality Engineering Responsibilities ; AI Architecture EngineeringDefine and own AI reference architectures for generative AI, agentic systems, and AI augmented applicationsArchitect scalable solutions using LLMs, multi agent systems, orchestration frameworks, and AI pipelinesDesign AI platforms supporting model serving, prompt management, RAG, and workflow orchestrationEstablish architectural standards for performance, scalability, reliability, and cost efficiencyPlatform Engineering IntegrationBuild reusable AI components for LLM integration, vector search, embeddings, and inference servicesEnable secure and scalable deployment using Kubernetes, serverless platforms, and CI/CD pipelinesIntegrate AI capabilities into enterprise systems using APIs, SDKs, and event driven architecturesCollaborate with QE teams to embed AI into test automation, test data generation, and intelligent validation Technical and Professional Requirements: ; LLM AND (RAG OR "Retrieval Augmented Generation") AND(LangChain OR LangGraph OR CrewAI OR AutoGen) ANDPython AND Kubernetes, Agentic AI OR "Multi Agent Systems" OR"Autonomous Agents" OR"AI Orchestration", (AWS Bedrock OR Azure OpenAI OR Vertex AI) AND(Kubernetes OR Docker) AND(Microservices OR Cloud Native) Preferred Skills: ; Technology->Open System->Open System- ALL->Python Technology->AI Hyperscalers->Azure Agentic AI Services->Azure NLP Technology->AI Hyperscalers->Google Agentic AI Services->GCP Technology->Agentic AI->Google Cloud Contact Center AI Technology->AI Hyperscalers->AWS Agentic AI Services->AWS Neuron Technology->Machine Learning->Generative AI->retrieval augmented generation (rag) Technology->AI Engineering->AI/ML Solution Architecture and Design Technology->Agentic AI->Agent Engineering Technology->AI Engineering->Model Deployment (Kubernetes) Technology->Agentic AI->AgentOps