Generative Ai Engineer

With just over 7 years of experience in the Portuguese market, we share our DNA with more than 200 workers and position our offer according to 3 lines of service: Strategy (Outsourcing, NeXel, Team as a Service, Tech Academies); R&D (Bootcamps,POC, Tech Lab); Nearshore. In ADENTIS, we focus on PEOPLE. This is our emotional salary: Great Work-Life balance; Very flexible organizational routine; Health benefits(for you and your family); Team Building activities; Over 300 protocols to offer you great discounts in different areas; Continuous professional development sponsored by our Training and Certification Department; Regular feedback on your performance through a personalized plan; Comprehensive career plan and progression involving assertive performance reviews. Responsibilities: - Develop and implement generative AI models, including LLMs and multimodal architectures, for use cases such as content personalization, intelligent automation, semantic analysis, and assisted creation. - Create and manage automated data pipelines and fine-tuning workflows, ensuring efficient data processing, dataset preparation, and seamless integration of generative models into existing systems and workflows. - Enhance platform monitoring capabilities in alignment with the Data Science team to ensure the quality, consistency, and reliability of data used for training, evaluation, and inference of generative models. - Collaborate with Data Engineering (DE) and IT teams to identify and leverage data platforms that support the development of feature stores, pipelines, and dataset management for generative AI workloads. - Advance the MLOps/LLMOps discipline to include model versioning (model registry), dataset versioning, prompt management, and experiment tracking to support a robust experimentation environment. - Utilize Azure Databricks for data processing, model training, fine-tuning, and deployment, optimizing resources for efficient and cost-effective generative AI solutions. - Design and maintain scalable, high-performance infrastructure required to serve generative models in production environments. - Work closely with IT and DevOps teams to manage cloud resources and deployment environments, ensuring security, scalability, and performance of generative AI applications. You must have: - Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. - Proven experience as a Machine Learning Engineer, Generative AI Engineer, or similar role, preferably with exposure to CRM and platform-based solutions. - Proficiency in developing generative AI models, fine-tuning LLMs, working with embeddings, RAG techniques, and applying models for personalization, automation, and semantic understanding. - Experience with pipeline automation, data flow monitoring, and hands-on use of Azure Databricks for data processing, training, and deployment of generative models. - Familiarity with cloud infrastructure management, preferably within the Azure ecosystem, and strong programming experience with Python (and optionally R or Scala). - Proficiency with relevant frameworks and libraries such as Hugging Face Transformers, LangChain, PyTorch, TensorFlow, or similar tools. - Strong analytical and problem-solving skills, paired with excellent communication and collaboration abilities. - Familiarity with DevOps/LLMOps practices and tools, with experience in CRM platforms and customer data analytics considered an advantage. - EU Citizenship or Portuguese Working Visa / Residency. - Availability for in-office collaboration twice per month. If you want to be part of a real People First organization, join us Send your CV to