Architect AWS Cloud

Hace 6 días

Valencia, Valencia (comarca); Provincia de Valencia; Comunidad Valenciana, España Sngular Jornada completa
Overview In this role you will design and implement scalable Generative AI architectures that bring production-ready AI capabilities to multiple industries. You collaborate with cross-functional teams to define end-to-end AI patterns, from data pipelines to model deployment and monitoring. You will lead LLM-based systems, apply prompt engineering, and ensure secure, observable, cost-efficient AI solutions. This is a hands-on, architecture-driven position with a focus on impact and practical delivery. Compensaciones / Beneficios Wellbeing pack Budget for training Welcome pack Free Udemy access Birthday day off Career plan Responsabilidades Design scalable production AI architectures (Generative AI and ML) Define end-to-end AI solution patterns from data ingestion to deployment and monitoring Architect and implement LLM-based systems including RAG pipelines, agents, and orchestration frameworks Define model lifecycle strategies (training, deployment, monitoring, retraining) Design data and feature pipelines for AI/ML in cloud environments Ensure AI solutions are secure, scalable, observable, and cost-efficient Collaborate with Data, Software, and Cloud teams to integrate AI capabilities into platforms Define standards for AI governance, evaluation, and responsible AI usage Evaluate new AI technologies for business use cases Support prompt engineering strategies, evaluation frameworks, and AI experimentation Act as technical reference for AI architecture decisions across projects Requisitos principales Hands-on experience with generative models and AI agents in production Proficiency with Transformers, CNNs, GANs Expertise in prompt engineering (Chain-of-Thought, ReAct, Tree-of-Thought) Mastery of TensorFlow, PyTorch or similar frameworks NLP experience with embeddings, vector search, fine-tuning Experience orchestrating LLMs and conversational agents (LangChain, LangGraph, DSPy, CrewAI, Google ADK) LLM monitoring and evaluation using LangSmith, LangFuse or similar Data management at scale (SQL, NoSQL, FAISS, Pinecone, Weaviate, ChromaDB) Model optimization and deployment techniques (quantization, distillation, vLLM, Triton, ONNX Runtime) Cloud and DevOps for AI (Azure, AWS, GCP, SageMaker, Vertex AI, Azure AI Foundry, Kubeflow, MLflow, Metaflow, BentoML) API development for LLMs and pipelines (FastAPI, Flask, gRPC) Advanced Python programming Proactivity Teamwork in diverse environments Analytical thinking Python (Advanced) Generative AI Expertise (GPT, Claude, Mistral, Llama) Core AI Frameworks (TensorFlow, PyTorch)