Principal MLOps Architect
16 days ago
Palma
Principal MLOps Architect Location: Remote from Spain (an indefinite Spanish employment contract) We are seeking a highly experienced and hands-on Principal MLOps Architect & Applied AI Lead to drive the design, development, and operationalization of enterprise-scale AI systems across research and production environments. This role combines deep technical expertise in Machine Learning, Generative AI, distributed data systems, and cloud-native architectures with strategic leadership capabilities. The ideal candidate will lead complex AI initiatives end-to-end — from experimentation and research to scalable deployment in global enterprise environments. The position requires a strong balance between: • technical leadership,, • hands-on implementation,, • AI strategy,, • cross-functional collaboration,, • and mentoring of engineering and data science teams. Requirements: • Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field, • 10+ years of experience in AI/ML, data science, or distributed systems engineering., • Proven experience designing and deploying production-grade AI solutions at enterprise scale., • Strong background in both research and industrial AI environments., • Experience leading global or distributed technical teams., • Demonstrated success delivering AI transformation initiatives., • Large Language Models (LLMs), • Generative AI systems, • NLP / NLU, • Apache Spark, • Databricks, • Delta Lake, • SQL / NoSQL databases, • Distributed computing architectures, • Streaming and batch processing pipelines, • Azure and/or AWS, • Docker, • Kubernetes, • CI/CD pipelines, • Infrastructure-as-Code, • MLOps frameworks, • Python, • Scala, • Experience with AI governance and responsible AI practices., • Experience building AI platforms serving multiple teams or business units., • Experience optimizing cloud infrastructure and reducing operational costs. Responsibilities: • Lead the design and implementation of AI/ML solutions across multiple business domains., • Drive enterprise adoption of Large Language Models (LLMs), Generative AI, NLP/NLU, and advanced analytics solutions., • Define AI architecture standards, MLOps best practices, and scalable deployment strategies., • Evaluate emerging AI technologies and identify opportunities for innovation and operational impact., • Translate research initiatives into production-ready AI solutions., • Architect scalable distributed data-processing systems capable of handling large-scale datasets and real-time pipelines., • Design and optimize cloud-native AI platforms using modern data engineering frameworks., • Lead cloud migration and modernization initiatives from on-premises environments to Azure and/or AWS., • Implement efficient data pipelines leveraging Spark, Delta Lake, Databricks, Kubernetes, and containerized environments., • Ensure reliability, scalability, observability, and cost-efficiency of AI infrastructure., • Design and implement enterprise-grade chatbot and conversational AI platforms., • Lead development of Retrieval-Augmented Generation (RAG), agentic workflows, and LLM orchestration systems., • Define governance, evaluation, and monitoring strategies for GenAI systems., • Collaborate with research teams to operationalize LLM-based applications securely and responsibly., • Lead cross-functional teams composed of data scientists, ML engineers, software engineers, and business stakeholders., • Mentor engineers and researchers in AI/ML best practices, architecture, and software engineering standards., • Coordinate global AI initiatives across distributed teams and multiple geographies., • Communicate technical concepts effectively to executive and non-technical audiences., • Support innovation programs and AI adoption strategies across the organization.
