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Mid-level Data & AI Engineer (m/f)

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Onsite

Mid-level Data & AI Engineer (m/f)

ARHS

Mid-level Data & AI Engineer (m/f)

Skills

DockerTypescriptPythonData ScienceJavaSpring BootData AnalysisMachine LearningAIAWSAnsibleGitHubNLP / Natural Language ProcessingFastAPITerraformAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Luxembourg

Work mode:

Onsite

Published on:

12 August 2026

What they need


Arηs Group, Part of Accenture, specializes in the management of complex public sector IT projects, including systems integration, informatics and analytics, solution implementation and program management. Our team helps lead clients through digital and information systems design, bringing expertise in a variety of areas ranging from software development, data science and security management to machine learning, cloud, and mobile development.

Arηs Group was acquired by Accenture in July 2024.

ARHS Group, part of Accenture, is looking for a Data & AI Engineer (Mid-level) to join our team in Luxembourg.

In this role, you will contribute to the design, development, and deployment of AI solutions across NLP, computer vision, and LLMs, from edge devices to cloud infrastructure. You will work alongside experienced engineers to transform raw data into secure, high-performing AI-driven solutions and contribute to the continuous improvement of our Machine Learning practices.

THE WORK:

  • Design and implement AI/ML pipelines covering data ingestion, feature engineering, model training, deployment, and post-deployment monitoring.
  • Develop and customize LLM-based solutions, including open-source models such as Mistral and LLaMA, on hybrid cloud and on-premises infrastructure.
  • Build NLP pipelines for information extraction, classification, semantic search, and document understanding.
  • Develop production-ready AI services and APIs using FastAPI or equivalent frameworks.
  • Deploy AI workloads to cloud platforms (Azure and/or AWS) and edge devices such as NVIDIA Jetson Orin and Xavier NX.
  • Contribute to infrastructure automation and reproducible ML environments using Terraform, Ansible, and Docker.
  • Integrate AI components into event-driven and serverless environments such as Azure Functions and Event Grid.
  • Contribute to MLOps practices, CI/CD processes, observability, and continuous improvement of AI solutions.
  • Collaborate with software, cloud, and data engineers to deliver maintainable and scalable AI solutions.

Our roles require in-person time to encourage collaboration, learning, and relationship-building with clients, colleagues, and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.

The work location for this role is an ARHS – Part of Accenture office.

HERE’S WHAT YOU’LL NEED:

  • 3+ years of hands-on experience in AI/ML engineering, contributing to the delivery of production-ready AI solutions.
  • Programming & APIs: Python, REST APIs, performance optimization, and secure API development.
  • NLP & ML: Transformers, LLMs (Mistral, LLaMA, etc.), RAG architectures, prompt tuning, vector search, OCR pipelines, and chatbot development.
  • Cloud Platforms: Experience with Azure and/or AWS services.
  • MLOps & Infrastructure: Docker, GitHub Actions, Infrastructure as Code (Terraform, Ansible), and CI/CD pipelines.
  • AI System Integration: Familiarity with edge inference, Ollama/ONNX runtime, hybrid deployments, and workload orchestration.
  • Strong analytical and problem-solving skills with an interest in building clean, documented, and maintainable AI solutions.
  • Ability to work autonomously on assigned topics while collaborating effectively with the wider engineering team.
  • Familiarity with Agile and DevOps practices.
  • Strong communication skills in English or French; knowledge of both is a plus.

BONUS POINTS IF YOU HAVE:

  • Experience with traditional software development technologies such as Java, .NET, TypeScript, or Spring Boot.
  • Experience deploying AI workloads to edge devices.
  • Knowledge of event-driven and serverless architectures.
  • AWS and/or Azure certifications.
  • Interest in knowledge sharing and contributing to internal AI/ML engineering practices.

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