DontApply.Club
Login Register

Data & AI Engineer

Avanade — Poland · Posted ~10 hours ago

Skills

Azure AI Azure OpenAI Azure AI Foundry Azure Cognitive Services AI solution development Data engineering Data pipelines ETL Enterprise data integration Microsoft Azure

🔓 Log in to save this job, tailor your resume & track your apply process — 7 days free, no card needed.

Log in to add to target list

Summary ✨ AI‑Generated

Join a data and AI engineering team building intelligent solutions on a major cloud platform. You’ll develop AI applications, integrate AI components with enterprise data systems, build pipelines and ETL workflows when needed, and evaluate emerging capabilities for practical use. The role suits an engineer comfortable across both AI and data engineering.

Highlights

Work on modern AI and data engineering solutions across diverse industries, with opportunities to build practical AI applications, collaborate with engineering teams, and explore emerging AI capabilities.

Description

Come join us We’re seeking a Data & AI Engineer to design and deliver intelligent solutions on Azure using modern data practices. You’ll contribute to cross-industry projects that bring together Azure OpenAI, Azure AI Foundry, and other leading AI capabilities. When required by the project, you’ll also take on Data Engineering work—building data pipelines and implementing ETL processes. What You’ll Do Build and release AI solutions using Azure OpenAI and related Azure AI servicesConnect AI components with enterprise data platforms, pipelines, and operational systemsPartner with data engineers to ensure high-quality, well-structured data feeds AI workflowsPrototype and evaluate emerging AI features, turning them into practical client-facing improvementsStep into a Data Engineering role when a project calls for it Qualifications Skills and experiences To Succeed In This Position, You Should Have Proven experience with the Azure AI stack (OpenAI, AI Foundry, Cognitive Services)Strong Python skillsComfort translating AI concepts into clear guidance for both technical and non-technical audiencesWorking knowledge of prompt engineering techniquesSolid grasp of data engineering fundamentals (ETL, data modeling)Experience with ML frameworks such as PyTorch and TensorFlowIdeally, practical exposure to data engineering platforms and tools such as Databricks, ADF, MS FabricEnglish at B2 level (or higher)