4 months 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 to improve AI model performance and reliability in production.
- Translate business requirements and operational challenges into AI use cases and intelligent workflows.
- Contribute to agentic AI systems and orchestration architectures that are robust, scalable, and aligned with enterprise governance.
- Track developments in AI models, tools, and frameworks and incorporate relevant innovations into team practices.
- Document methodologies, prompt libraries, and context engineering standards for reusable institutional knowledge.
- Collaborate with central and local data teams and business stakeholders in an international environment.
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; Python is a plus 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 knowledge of data science principles including data quality, lineage, semantics, and governance.
- Awareness of current AI developments, including leading LLMs, multimodal models, agentic frameworks, and orchestration tools.
- Practical experience with knowledge graphs, ontologies, or semantic data models is preferred.
- Ability to translate real-world business challenges into well-designed AI workflows.
- Strong communication skills and ability to explain complex AI concepts to non-specialists.
- Fluency in English; additional languages and experience in international, consulting, or scale-up environments are advantageous.
Benefits
- Opportunity to work in an emerging applied AI discipline with scope to help define its practice within a large organization.
- Deep technical exposure across data foundations, knowledge graphs, agentic systems, LLM orchestration, and the broader AI stack.
- Collaboration with central and local data teams and business stakeholders.
- Opportunity to build reusable AI assets and infrastructure that create value at scale.
- Collaborative, diverse culture emphasizing experimentation, continuous learning, knowledge sharing, and professional growth.
- Position based in Porto.
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