4 hours ago
Porto, PortugalEntry Level / Mid Level
Responsibilities
- Design, implement, and continuously refine AI solutions and products from prototyping through production deployment.
- Define, create, and maintain an AI-optimized organizational context layer, including knowledge graphs, ontologies, governance graphs, data lineage frameworks, and RAG pipeline architectures.
- Apply prompt engineering, context engineering, memory engineering, and harness engineering techniques to improve AI model performance and reliability.
- Translate business requirements and operational challenges into AI-enabled use cases and workflows.
- Contribute to robust, scalable agentic AI systems and AI orchestration architectures aligned with enterprise governance requirements.
- Monitor AI developments and incorporate relevant models, tools, and frameworks into team practices.
- Document methodologies, prompt libraries, and context engineering standards to create reusable institutional knowledge.
Requirements
- 1–4 years of professional experience as a software engineer, data scientist, data engineer, or AI engineer.
- Strong programming skills in at least one modern language, with Python preferred but not required.
- Proficiency with Git and solid software engineering practices.
- Hands-on experience building LLM-based systems, including prompt engineering and at least one orchestration framework such as LangChain, LlamaIndex, or LangGraph.
- Solid understanding of Retrieval-Augmented Generation pipelines and their design considerations.
- Strong understanding of data science principles, including data quality, lineage, semantics, and governance.
- Awareness of leading LLMs, multimodal models, agentic frameworks, and orchestration tools.
- Practical experience with knowledge graphs, ontologies, or semantic data models is preferred.
- Ability to combine technical rigor with business understanding and explain complex AI concepts to non-specialists.
- Fluency in English; additional languages and experience in international, consulting, or scale-up environments are preferred.
Benefits
- Opportunity to define applied AI practices within a large organization.
- Technical exposure across data foundations, knowledge graphs, agentic systems, and LLM orchestration.
- Collaboration with central and local data teams and business stakeholders.
- Opportunity to build reusable AI assets and infrastructure at scale.
- Experimentation, continuous learning, and knowledge sharing within a global and diverse team.
- Based at the HUGO BOSS Digital Campus in Porto.
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About Metyis AG
Metyis AG is a privately held consulting firm that delivers AI and data analytics, digital commerce, marketing/design, and advisory services to enterprises. It partners with B2B and B2C clients to build data platforms, e‑commerce capabilities, and operating models, typically through long-term engagements. Founded in 2013 and headquartered in Baar, Zug, the company operates from 14 offices across Europe, India, and the Middle East.