Final-Year Internship – R&D Data & AI Engineer

Imagine, build, and industrialize the Data & AI platforms of tomorrow!

Who are we?

At keyIT, we support Swiss companies in their digital transformation by combining Cloud, cybersecurity, Data Engineering, and artificial intelligence. We design modern, high-performance, and secure solutions tailored to business needs and requirements for data governance, sovereignty, and control.

Our teams are involved at every stage, from consulting and architecture to integration, automation, and operations.

As part of the expansion of our Data & AI activities and R&D initiatives, we are looking for a final-year intern eager to contribute to the next generation of Data and AI platforms.
 

The challenge we offer
With public Cloud, sovereign infrastructures, generative AI, and evolving governance requirements, Data architectures are changing rapidly.

Your objective will be to explore how to combine the power of the Cloud with data control and security, interoperability, reversibility, and sovereignty, before developing a production-ready, intelligent, automated, and reusable platform.

You will contribute to a genuine applied research and engineering project, combining technology benchmarking, architecture design, development, experimentation, and the creation of a working prototype.
 

Your responsibilities

1. Data Sovereignty and Hybrid Architectures

  • Research sovereign Data platforms and Swiss hosting and Cloud providers.

  • Compare public, private, and hybrid Cloud environments, as well as open-source solutions.

  • Analyze data residency, confidentiality, security, interoperability, and reversibility.

  • Evaluate technological, operational, and economic trade-offs.

  • Propose reference architectures tailored to Swiss businesses.
     

2. Infrastructure, Automation, and DevSecOps

  • Explore Cloud-native and highly available architectures.

  • Automate infrastructure provisioning using Terraform or OpenTofu.

  • Implement Infrastructure as Code (IaC), DevSecOps practices, and CI/CD pipelines.

  • Integrate identity management, secrets management, private connectivity, and observability.

  • Develop modular, configurable, and reusable components.
     

3. Governed Data Engineering Platform

  • Design data ingestion, transformation, and delivery pipelines.

  • Experiment with Data Warehouse, Lakehouse, and DataHub architectures.

  • Integrate Data Quality, Data Lineage, data cataloging, and Data Governance.

  • Implement security policies and access controls.

  • Develop reusable transformation models and components.
     

4. Semantic Models and Artificial Intelligence

  • Explore Semantic Layers, Knowledge Graphs, and business knowledge modeling.

  • Experiment with LLMs, RAG, and AI agents to unlock the value of data.

  • Develop a use case for intelligent querying of governed data.

  • Evaluate the security, traceability, reliability, and explainability of AI-generated responses.

  • Explore AI applications for administration, diagnostics, and automation.
     

5. Industrialization and Reusability

  • Design a deployment framework for Data & AI platforms.

  • Develop IaC modules, templates, and standardized pipelines.

  • Package components for deployment across different environments.

  • Test reproducibility, robustness, portability, and performance.

  • Document findings and recommend next steps toward industrialization.
     

What you will actually build
This internship is not intended to be a purely theoretical study or a series of disconnected proof-of-concepts (POCs).

You will design and develop an integrated demonstrator, supported by well-reasoned technical decisions. The project scope will be defined together with your supervisor to ensure it is achievable and provides valuable material for your final-year thesis.

Your key deliverables will include:

  • Technology benchmark: A comparative assessment and evaluation framework for hybrid and sovereign architectures.

  • Reference architecture documentation: Technical choices, data flows, security considerations, and deployment scenarios.

  • Automated infrastructure foundation: IaC modules, CI/CD pipelines, and reproducible configurations.

  • Functional Data & AI prototype: Data ingestion, transformation, governance, semantic modeling, and intelligent data consumption.

  • Reusable framework: A documented, tested, and adaptable technical framework.

  • Experimentation report: Performance analysis, results, limitations, and recommendations.
     

Technology Stack

  • Cloud & Infrastructure: Microsoft Azure, Swiss Cloud providers, Kubernetes, Docker, Terraform, OpenTofu

  • Data Engineering: Azure Databricks, Microsoft Fabric, Python, SQL, PySpark, dbt, Lakehouse

  • DevOps: Git, Azure DevOps, CI/CD, IaC, automation, observability

  • Data Governance: Data catalogs, Data Lineage, access control, semantic models, metadata

  • Artificial Intelligence: LLMs, RAG, AI agents, LangGraph, APIs, orchestration

Please note: These technologies represent potential areas of exploration. You are not expected to have experience with all of them.


Who are we looking for?

You are in the final year of an engineering degree or Master's program, specializing in Computer Science, Software Engineering, Data Engineering, Cloud Computing, or Artificial Intelligence.

You have a solid foundation in software development, Python, SQL, and Git, along with a strong interest in modern technology architectures.

You enjoy tackling complex challenges, experimenting with new technologies, and finding innovative solutions.

Above all, we value curiosity, analytical thinking, attention to detail, independence, a willingness to learn, and the ability to explain and justify technical decisions.

We are not looking for someone who is already an expert in every technology.
 

Why join keyIT?

  • Research & Development: Work on a relevant and strategically important technology challenge.

  • Mentorship: Learn from and collaborate with our experienced consultants and architects.

  • Hands-on Experience: Build practical, reusable technical accelerators.

  • Cross-functional Exposure: Gain experience across architecture, automation, governance, and AI.

  • Academic Value: Develop a demonstrable and well-documented prototype for your final-year project.
     

Practical Information

  • Position type: Final-year engineering / Master's internship

  • Duration: 5–6 months

  • Start date: From February 2027, flexible depending on your academic schedule

  • Location: Marly (Fribourg) or Vernier (Geneva), French-speaking Switzerland

  • Supervision: Data & Cloud / Architecture & R&D Team

  • Application: CV and a few lines explaining your interest in the project

     

Ready to turn your final-year project into a real-world research, innovation, and engineering experience?

Apply directly by sending your CV and a short motivation statement to hr@keyit.ch.

Email subject: Final-Year Internship – R&D Data & AI – 2027