Who we are

www.lnds.lu | LNDS on LinkedIn

Purpose of the job / project

As an AI Engineer, you will be part of the DataOps team and work closely with the service delivery team to design and implement AI-powered solutions that enhance LNDS services offered to partners. This includes:

• integrating LLMs and other AI technologies into service workflows

• building internal tools and agents

• improving how teams deliver, combine, and scale services.

You will work in a GNU Linux/Unix-first, FOSS-oriented environment and contribute through disciplined engineering, careful experimentation, and clear documentation. The role focuses on applied AI engineering: turning real operational and service needs into practical, reliable solutions rather than developing models from scratch.

What you will do

Contribute to improving LNDS services by integrating AI into service delivery workflows
Build and support AI-powered tools, agents, assistants and internal applications to support internal teams and partner-facing activities
Help simplify and accelerate service delivery by automating repetitive or manual tasks
Assist with evaluating, testing, and integrating AI/ML models and related tooling for internal use cases
Design and implement basic evaluation and benchmarking approaches for AI systems (e.g.,prompt evaluation, retrieval quality, system behaviour)
Contribute to AI workflow design, including data preparation, prompting strategies, evaluation and deployment patterns
Help improve the reliability, reproducibility, and maintainability of AI development practices
Contribute to ensure that AI systems are deployed responsibly, with appropriate validation(including human in the loop where needed) and awareness of privacy, risk, accuracy, and context
Contribute to AI-driven initiatives such as domain-specific applications (e.g., knowledge systems, legal or regulatory use cases, internal assistants)
Work productively with FOSS-based tools and frameworks in a Unix/Linux environment
Document technical decisions, implementation details, and operational procedures clearly and accurately. Collaborate with technical and non-technical colleagues to translate internal needs into practical solutions. Contribute to the responsible, sustainable adoption of AI across the organisation
Contribute to EU projects as required.

Who you are

BSc or MSc in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Mathematics, Physics and related fields
2–5 years of relevant experience in AI, machine learning, software engineering, data science, and a related technical area
Good grounding in Python and sound software engineering practices
Hands-on experience with Unix/Linux environments as a primary platform
Hands-on experience with LLMs-based systems (RAGs, assistants, workflow automation, agentic systems or model evaluation)
Practical familiarity with open-source tools, libraries and development workflows
Ability to work independently on well-scoped tasks and solve problems in a structured way• High standards of accuracy, reliability and technical discipline
Sensitivity to internal user needs and ability to iterate based on feedback
Experience of working in Agile-minded teams
Strong written and verbal communication skills and willingness to learn.

Nice to have (considered as advantages):

Awareness of data privacy, security, and responsible AI considerations in system design
Familiarity with containers, REST, CI/CD or MLOps-related tooling
Exposure to vector or graph databases, experiment tracking, model serving, or observability tooling
Contributions to open-source projects or demonstrable personal technical projects