6 meilleures offres (python platform engineer devops, paris, a8) (à pourvoir)

AI Engineer / Agent Developer
Metyis AG —Paris (75)
- Temps plein
- Télétravail partiel
- Azure
- SQL
- Niveau Licence
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il y a 1 jour
Lead Data Platform Engineer (IT) / Freelance
RED Commerce - The Global SAP Solutions Provider —Paris (75)
- Azure
- SQL
- Python
18 h
Software Engineer I
Checkout.com —Paris (75)
- Temps plein
- Azure
- Master
- Bases de données
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il y a 1 jour
Senior Data Architect
Axway Software SA —Courbevoie (92)
- DevOps
- AWS
- Python
- Horaires flexibles
il y a 14 jours
Consultant Senior H/F - Cloud Architect Expert GCP
Sopra Steria Next —Courbevoie (92)
- Temps plein
- Télétravail partiel
- Azure
- Informatique
- DevOps
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Data Engineer GCP H/F
Open SAS —Levallois-Perret (92)
- SQL
- Python
Postuler rapidement

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Lead Data Platform Engineer (IT) / Freelance
RED Commerce - The Global SAP Solutions Provider —Paris (75)
Déployer et gérer l?infrastructure avec Docker, DBT, SQL et des outils DevOps (CI/CD, monitoring, alerting). Expérience avec Microsoft Azure (Microsoft Fabric…
18 h

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AI Engineer / Agent Developer

Metyis AG
Paris (75)

Postuler rapidement

Détails de l'emploi

Temps plein
Il y a 1 jour

Qualifications

Azure
SAP HANA
SAP
Git
SAP BW/4HANA
Développement d'applications
SQL
Assurance qualité
Niveau Licence
APIs
Securité
SAP ERP
Intelligence artificielle
ABAP
Compétences en communication
Python

Description complète du poste

Metyis is growing! We are looking for a AI Engineer/ Agent Developer with +4 years of relevant experience for a full-time position to join the Technology team at our Digital Campus in Porto.

Who we are

We are Metyis, a forward-thinking, global company that develops and delivers solutions around Big Data, Digital Commerce, Marketing and Design and provides Advisory services. We have offices in 15 locations with a talent pool of 1000+ employees and more than 50 nationalities, dedicated to creating long-lasting impact and growth for our business partners and clients.

Together with HUGO BOSS, our esteemed business partner, we have embarked on a joint venture and created the HUGO BOSS Digital Campus, dedicated to increasing the data analytics, eCommerce and technology capabilities of the company and boosting digital sales. The HUGO BOSS Digital Campus employees will help create a state-of-the-art data architecture infrastructure, advanced business analytics, and the development and enhancement of HUGO BOSS’ eCommerce platform and services.

This collaborative environment will provide the capabilities required for HUGO BOSS to maximise data usage and support its growth trajectory towards becoming the leading premium tech-driven fashion platform worldwide.

What we offer

Develop your professional career working with one of the major brands in the fashion industry
Lead a fast-growing international and diverse team
Driving to success a best in class E2E demand and supply planning initiative to improve the whole supply chain of the entire organization
Working with a world leading software vendor and one of the most advanced integrated business planning platforms in the world
Driving high-impact insights enhances decision-making across the entire organization

What you will do

Design, develop, and maintain AI-powered agents, copilots, and automation solutions supporting SAP migration and enterprise data platform modernization.
Build scalable backend services, APIs, orchestration workflows, and automation components for AI-enabled migration solutions.
Develop AI capabilities that analyze SAP BW objects, ABAP code, metadata, lineage, dependencies, interfaces, and migration complexity.
Build Retrieval-Augmented Generation (RAG) and context-management solutions using enterprise documentation, metadata, business rules, code repositories, and data catalogs.
Integrate AI applications with SAP repositories, DevOps pipelines, documentation platforms, source control systems, and enterprise data platforms.
Support migration activities including object discovery, impact analysis, source-to-target mapping, documentation generation, reconciliation, testing, and validation.
Partner with SAP Architects and domain experts to convert business knowledge into reusable AI context, structured metadata, and intelligent automation.
Implement human-in-the-loop review processes, approval workflows, traceability, and quality controls for AI-generated outputs.
Ensure AI solutions meet enterprise standards for security, governance, monitoring, observability, and responsible AI.
Contribute to reusable AI frameworks, development standards, automation accelerators, and engineering best practices

What you will bring

4+ years of experience in Software Engineering, AI Engineering, Data Engineering, Automation, or Enterprise Application Development.
Strong proficiency in Python and experience building production-grade applications, APIs, backend services, or automation platforms.
Hands-on experience developing AI applications using LLMs, AI agents, Retrieval-Augmented Generation (RAG), tool/function calling, and workflow automation.
Experience integrating AI solutions with enterprise applications, APIs, databases, documentation platforms, DevOps tools, and code repositories.
Strong understanding of software engineering best practices including Git, CI/CD, automated testing, secure development, code quality, and observability.
Experience working with Microsoft Azure, Azure AI Services, Azure OpenAI, Azure AI Foundry, Databricks, Microsoft Fabric, or similar cloud platforms.
Strong SQL and data analysis skills with experience validating data, investigating discrepancies, and working with source-to-target mappings.
Knowledge of enterprise data platforms, metadata management, data lineage, data quality, and analytics.
Understanding of AI governance, security, responsible AI principles, model evaluation, and enterprise access controls.
Excellent analytical, problem-solving, and stakeholder communication skills.

Nice to Have

Experience with SAP BW, SAP HANA, ABAP, SAP metadata, extractors, APIs, or SAP integration patterns.
Experience supporting SAP modernization, ERP migration, or enterprise transformation initiatives.
Exposure to automating technical documentation, code analysis, testing, migration support, or reconciliation processes.
Experience implementing human-in-the-loop AI workflows, evaluation frameworks, and quality assurance controls.
Experience collaborating across AI, Data Engineering, SAP, BI, CloudOps, and enterprise architecture teams.

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