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  • Omilia
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Senior Data Architect will own the Training Environment data architecture, including dataset design, data selection strategy, and annotation pipeline architecture. Responsibilities include defining data quality frameworks, building the data catalog, and architecting the data flywheel. Requires 5+ years of experience in data architecture, data engineering, or LLM/ML data infrastructure. Strong understanding of ML training data requirements and experience with Snowflake, AWS S3, and ETL/ELT tools are essential.
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  • Finom
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Designs, builds, and operates AI systems to solve business problems across Finom. Focuses on delivering production-grade AI capabilities with a hands-on engineering approach. Collaborates with teams to integrate AI into workflows and improve existing systems.
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Defect Manager with 10+ years of experience needed for a full-time, hybrid position in Lisbon. Responsibilities include owning the defect approach and strategy, managing the defect process, triaging defects, and coordinating retests. Requirements include experience in QA/Defect Management, strong understanding of SDLC and Agile processes, and proficiency in JIRA, Zephyr, Azure DevOps, or similar tools. ISTQB Foundation Certificate is required.
  • Thinknology
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MuleSoft Developer needed for integration application and API design, development, and deployment. Requires proficiency in Anypoint Platform, DataWeave, RESTful and SOAP APIs, and API-led connectivity. Experience with MuleSoft connectors, adapters, and security best practices is essential.
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Skilled auditor to undertake audit missions across global operations. Focus on operational audits, financial reviews, and internal controls assessments. Effective communication of audit conclusions to local management. 2-3 years' experience in a Big 4 audit firm or equivalent required. High fluency in English and experience in international environments essential.
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The Generative AI Engineer designs, builds, and deploys production-ready AI-powered applications using Generative AI, Machine Learning, and LLM-based technologies. This role involves building RAG solutions, prompt-based systems, AI agents, embeddings, and semantic search, integrating LLM APIs, and developing backend services.