AI Solutions Engineer
Who we are
Adaptfy is a turnkey data & analytics solution for the SHV family of companies. We support multiple SHV Groups with advanced Data & Analytics in all areas, elevating their operations in diverse industries across international markets and throughout entire valuechains.
Adaptfy is a joint venture formed by SHV and Metyis. Metyis embodies visionary thinking in the digital world, while SHV is a globally established family of companies built on the values of integrity, trust, curiosity, passion, and inclusivity.
SHV has a presence across four continents, with businesses spanning energy, heavy lifting and transport, animal nutrition & aquaculture, testing, inspection & certification, and more. The organisation’s history reflects its courage to care—for people, for performance, and for future generations. Their success is a testament to constant reinvention through innovation.
At Adaptfy, we play a pivotal role in bringing SHV’s digital vision to life. From optimising supply chains across Europe to enhancing operational efficiency in South America, we connect the dots for SHV, shaping a data-driven future for the entire family of companies.
What we offer
The opportunity to work in one of the most rapidly evolving areas of applied AI and develop hands-on experience with emerging AI technologies.
Exposure to the full AI stack, including data foundations, knowledge management, RAG, LLMs, and AI-powered applications.
Close collaboration with experienced data and AI professionals, as well as business stakeholders, providing opportunities to learn across both technical and business domains.
The chance to contribute to AI solutions and reusable assets that create tangible business value.
A culture of experimentation, continuous learning, and knowledge sharing within a global and diverse team.
What you will do
Support the development, testing, and continuous improvement of AI solutions and products across different stages of the lifecycle, from prototyping to deployment.
Work with central and local data teams to help prepare and maintain data and context foundations for AI use cases, including data sources, knowledge bases, and RAG pipelines.
Support the implementation and testing of prompts, context strategies, and other techniques to improve the performance and reliability of AI applications.
Work with senior team members to understand business requirements and help translate operational challenges into practical AI use cases and workflows.
Research and experiment with new AI models, tools, and frameworks, sharing relevant findings and learnings with the team.
Contribute to the development and testing of AI agents and orchestration workflows under the guidance of more experienced team members.
Help document AI solutions, methodologies, prompts, experiments, and learnings to support knowledge sharing and reuse.
Support the team in monitoring AI solutions, identifying issues, and implementing improvements based on feedback and performance.
What you will bring
1–2 years of professional experience in software engineering, data science, data engineering, AI, or a related technical field. Relevant internships or academic projects are also valued.
Basic to intermediate programming skills in at least one modern programming language; Python is a plus.
Familiarity with Git and basic software engineering practices.
Some hands-on exposure to LLM-based applications, prompt engineering, or generative AI through professional, academic, or personal projects.
Basic understanding of Retrieval-Augmented Generation (RAG) and how it can be used to connect AI models with external data.
Understanding of fundamental data concepts, including data quality, data structures, semantics, and governance.
Awareness of the current AI landscape, including LLMs, multimodal models, AI agents, and emerging AI tools and frameworks.
Exposure to knowledge graphs, ontologies, semantic data models, or orchestration frameworks is a plus.
Strong analytical and problem-solving skills, with an interest in applying technology to real-world business challenges.
Ability and willingness to learn quickly and work collaboratively with more experienced technical and business colleagues.
Good communication skills, with the ability to explain technical concepts clearly.
Fluency in English; additional languages are a plus.
Experience in international, consulting, or scale-up environments is a plus.