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 / Ventajas

- 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)

📌 AI Architect (Hands-on) (España)
🏢 Sngular
📍 España