AI Architect (Hands-on)
9 hours ago
Bilbao
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)