Ingeniero/a IA Generativa- procesamiento documental datos sensibles

Accountabilities:

• Design and implement Generative AI solutions using advanced RAG architectures and intelligent information retrieval frameworks.


• Develop scalable systems for processing, structuring, and managing large volumes of complex and sensitive documentation.


• Define, optimize, and maintain vector databases to support efficient semantic search and AI-powered retrieval capabilities.


• Build and enhance ETL pipelines for data ingestion, transformation, enrichment, and processing across distributed environments.


• Implement and optimize chunking, prompting, and reranking strategies to improve AI model performance and response accuracy.


• Contribute to the continuous improvement, scalability, and technical evolution of AI solutions deployed in production environments.


• Collaborate with multidisciplinary teams in agile environments to deliver innovative and high-impact AI-driven solutions.


• Support best practices around information governance, data quality, and secure handling of sensitive information.


• Participate in technical discussions related to AI architectures, infrastructure optimization, and emerging Generative AI technologies.


• Help identify opportunities to improve operational efficiency, model reliability, and overall AI system performance.

Requirements

• Proven experience processing and managing large volumes of documents and complex information in enterprise environments.


• Strong hands-on experience designing, implementing, and maintaining vector databases and RAG-based architectures.


• Knowledge of sensitive data handling practices, secure information processing, and governance considerations.


• Experience building and optimizing ETL processes and large-scale data transformation workflows.


• Solid understanding of chunking strategies, prompt engineering, and reranking techniques for Generative AI applications.


• Familiarity with modern AI frameworks, LLM ecosystems, and enterprise AI deployment practices.


• Knowledge of caching strategies, resource optimization, and scalable AI infrastructure is considered advantageous.


• Experience fine-tuning LLMs or SLMs is highly desirable.


• Familiarity with graph-based databases and GraphRAG/KAG architectures is considered a strong asset.


• Experience working with Spark or distributed data processing environments is beneficial.


• Strong analytical thinking, problem-solving skills, and ability to work collaboratively in agile and fast-paced technical teams.


• Excellent communication skills and continuous learning mindset focused on innovation and emerging AI technologies.

• Permanent employment contract with competitive compensation package.


• Fully remote work environment offering flexibility and strong work-life balance.


• Personalized career development plans with ongoing training and continuous learning opportunities.


• Opportunity to participate in innovative and technically advanced AI projects within the financial sector.


• Flexible working hours designed to support productivity and personal balance.


• Access to social benefits and employee support programs tailored to individual needs.


• Exposure to cutting-edge Generative AI technologies, modern data architectures, and enterprise-scale solutions.


• Collaborative international environment focused on innovation, technical excellence, and professional growth.


• Stable long-term projects with high technical impact and strong career progression opportunities.

This listing is from ats_lever. View original listing ↗