AI Solutions Engineering Analyst

Location: Porto, Portugal

Company

hirify.global is a global consulting firm delivering AI and data, digital commerce, marketing and design, and advisory solutions across multiple industries.

What you will do

• Support the development, testing, and continuous improvement of AI solutions from prototyping through deployment.
• Prepare and maintain data sources, knowledge bases, context foundations, and RAG pipelines with central and local data teams.
• Implement and test prompts, context strategies, and other techniques that improve AI application performance and reliability.
• Translate business requirements and operational challenges into practical AI use cases and workflows.
• Research AI models, tools, and frameworks, and contribute to AI agents and orchestration workflows.
• Document solutions, experiments, prompts, and learnings, while monitoring systems and implementing improvements.

Requirements

• 1–2 years of experience in software engineering, data science, data engineering, AI, or a related technical field; relevant internships and academic projects are valued.
• Basic to intermediate programming skills in at least one modern programming language; Python is an advantage.
• Familiarity with Git and basic software engineering practices.
• Hands-on exposure to LLM applications, prompt engineering, generative AI, or RAG.
• Understanding of data quality, data structures, semantics, governance, and current AI technologies including multimodal models and AI agents.
• Fluent English and strong analytical, communication, problem-solving, and collaboration skills are required.

Nice to have

• Exposure to knowledge graphs, ontologies, semantic data models, or orchestration frameworks.
• Experience in international, consulting, or scale-up environments.
• Additional language skills.

Culture & Benefits

• Hands-on experience with applied AI and emerging AI technologies.
• Exposure to the full AI stack, including data foundations, knowledge management, RAG, LLMs, and AI-powered applications.
• Collaboration with experienced data and AI professionals and business stakeholders.
• Opportunities to contribute to reusable AI assets that create business value.
• Experimentation, continuous learning, knowledge sharing, and an inclusive global team environment.