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AI Architect (Hands-on)

On-site in Spain·Added today

Sngular

6 open roles

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Overview

Requirements

Have the right to work in Spain
Sngular doesn't mention sponsorship in the ad.
Work in English
English is required, per the ad.
Work on-site in Spain
No relocation package mentioned.
Have 3+ years of experience
Mid-level role.

Requirements

What we're looking for

Machine Learning & Deep Learning Models - Experience using and integrating generative models such as GPT, Claude, Mistral, or LLaMA. Knowledge of advanced architectures like Transformers, CNNs, GANs.
Advanced Prompting Techniques - Proficiency in prompt engineering (Chain-of-Thought, ReAct, Tree-of-Thought, etc.).
AI Frameworks - Mastery of TensorFlow, PyTorch, or similar tools.
Natural Language Processing (NLP) - Experience with embeddings (Word2Vec, FastText, BERT), vector search, and fine-tuning of pre-trained models.
Generative AI Development - Experience orchestrating LLMs and complex conversational agents using tools like LangChain, LangGraph, DSPy, CrewAI, or Google ADK. Knowledge of conversational flow design, structured content generation, and agent-based reasoning systems.
LLM Monitoring & Evaluation - Familiarity with observability tools and techniques for continuous model improvement in production, such as LangSmith, LangFuse, or similar tools for prompt tracking, debugging, and performance evaluation.
Large-Scale Data Management - Experience with structured and unstructured databases, Data Lakes, and vector databases such as FAISS, Pinecone, Weaviate, ChromaDB.
Model Optimization & Deployment - Knowledge of techniques like quantization and distillation, and efficient inference frameworks like vLLM, Triton, or ONNX Runtime. Familiarity with containerization and deployment in CUDA environments.
Cloud & DevOps for AI - Experience with Azure, AWS, or GCP, using tools such as SageMaker, Vertex AI, Azure AI Foundry, and MLOps frameworks like Kubeflow, MLflow, Metaflow, BentoML.
Integration & APIs - Development of APIs for LLMs, third-party tool integration, and pipeline implementation with FastAPI, Flask, or gRPC.
Advanced Programming - Expert-level proficiency in Python, with experience building scalable and robust systems.

The role

As an AI Expert or Architect, you will be responsible-together with the team-for designing solutions based on Generative AI. This requires a solid technical background and a hands-on approach, with proven experience in implementing language models and AI agents in various projects, including deploying real-world, moderately complex models to production.

What you'll do

- Design scalable AI architectures for production environments, including Generative AI and Machine Learning solutions.
- Define end-to-end AI solution patterns, from data ingestion to model deployment and monitoring.
- Architect and implement LLM-based systems, including RAG pipelines, agents, and orchestration frameworks.
- Define strategies for model lifecycle management, including training, deployment, monitoring, and retraining.
- Design data and feature pipelines for AI/ML systems 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 existing platforms.
- Define standards and best practices for AI governance, evaluation, and responsible AI usage.
- Evaluate emerging AI technologies and define their applicability in real business use cases.
- Support teams in designing prompt engineering strategies, evaluation frameworks, and AI experimentation approaches.
- Act as a technical reference for AI architecture decisions across projects.