PVisabeira ID is a leading innovation and research center based in Viseu and Lisbon, Portugal, dedicated to advancing technology and driving impactful solutions across industries.
Visabeira ID is part of bGrupo Visabeira /b, a diversified group with activity across areas such as btelecommunications /b, benergy /b, bconstruction engineering /b, bindustry /b, and btourism /b.
Our mission is to foster a culture of innovation, harnessing the power of data, artificial intelligence, and advanced engineering to build scalable, real-world applications.
/ppWe collaborate closely with Nearing Visabeira to turn operational documentation and field data into reliable, searchable knowledge.
Our focus starts with strong document ingestion, information extraction, and retrieval systems—then builds on that foundation with agentic AI and RAG experiences that help technicians access the right information quickly and take action with confidence.
/ppbr/ppData Scientist (Document Intelligence, Retrieval Agentic AI) /ppVisabeira ID – Viseu, Portugal /ppbr/ppRole Responsibilities /pulliDocument and speech processing (primary): Develop pipelines to ingest and process manuals, procedures, reports, and other unstructured content; integrate speech-to-text solutions to convert field audio into searchable text and structured signals.
/liliRetrieval and knowledge access: Build and improve retrieval systems (indexing, chunking, metadata, ranking) over internal knowledge bases, technical documentation, and operational data to maximize precision, recall, and freshness.
/liliAgentic AI and RAG: Design and implement LLM-based agent experiences that use the retrieval layer; build RAG pipelines that ground responses in trusted sources and support field workflows.
/liliTool integration and orchestration: Integrate agents and retrieval services with APIs, databases, and internal systems; design tool-calling/function-calling mechanisms so assistants can take actions (e.g., retrieve work orders, query equipment history, open tickets).
/liliEvaluation, safety, and reliability: Define qualitative and quantitative evaluation strategies (task success, user satisfaction, response quality); implement guardrails, policies, and monitoring to ensure safe, reliable, and compliant behavior in production.
/liliCollaboration and productization: Partner with project managers, domain experts, and field teams to translate workflows into robust use cases; collaborate with engineers to deploy and iterate on solutions across web, mobile, or internal tooling based on user feedback.
/liliInnovation and best practices: Stay current with advances in document intelligence, retrieval, LLMs, agentic AI, and evaluation techniques; promote best practices in data quality, retrieval design, prompting, evaluation, and lifecycle management.
/li /ulpbr/ppRequirements /pulliML NLP fundamentals: Solid grounding in machine learning and NLP; coursework and/or project work is OK.
/liliPython: Comfortable writing production-minded Python (clean code, notebooks + scripts).
/liliEngineering practices: Familiar with Git, basic testing, and building small APIs/services (or equivalent academic projects).
/liliData security: Awareness of data modeling, privacy, and security when working with internal documents and operational data.
/liliCollaboration languages: Portuguese and English required.
/liliAnalytical, interpersonal and planning skills are valued.
/li /ulpbr/ppBonus Qualifications /pulliExperience with document processing, search, or knowledge systems (e.g., OCR, information extraction, text classification, semantic search).
/liliExperience with vector databases and retrieval components used in RAG pipelines.
/liliExperience with RAG/agentic AI frameworks (e.g., LangChain, LlamaIndex, or similar).
/liliPrevious experience building chatbots or virtual assistants used in production environments.
/liliFamiliarity with field operations, utilities, telecom, infrastructure, or industrial domains.
/liliExperience integrating AI systems with mobile applications or tools used by technicians in the field.
/liliContributions to applied research, open-source projects, or internal frameworks in the area of LLMs, agents, retrieval, or RAG.
/li /ulpbr/ppVisabeira ID offers a competitive compensation package that reflects experience, qualifications, and the unique skills brought by each candidate.
Our benefits are designed to support professional growth and well-being, and we are committed to providing opportunities for advancement within a dynamic, innovative environment.
Specific salary details will be discussed during the interview process, considering both market benchmarks and individual expectations.
/ppbr/ppTo apply for the Data Scientist (Document Intelligence, Retrieval Agentic AI) position at Visabeira ID, please submit your resume and a brief cover letter highlighting your relevant experience to or .
For any questions about the role or application process, contact our HR team at the same email address.
/ppJoin us at Visabeira ID and Nearing Visabeira to shape the future of intelligent perception technologies!
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