AI Solution Architect @ Engenious
(práce v Polsku)

AI Solution Architect @ Engenious

Polsko

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 
• 10+ years of experience as a Solutions Architect or Technical Lead, with a strong focus on enterprise AI and data-driven solutions. 
• Deep hands-on experience with the Microsoft Azure ecosystem (e.g., Azure Machine Learning, Azure Cognitive Services, Azure OpenAI, Azure Synapse, Azure Data Lake). 
• Proven track record in designing and deploying AI solutions at scale, including model development, data pipelines, and MLOps within Azure environments. 
• Proficiency in programming languages such as Python or C#, and experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn. 
• Strong knowledge of modern architectural patterns and cloud-native development, including containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines. 
• Excellent analytical and communication skills; able to convey complex AI concepts to business and technical stakeholders alike. 
• Experienced in Agile development environments and familiar with frameworks such as Scrum or Kanban. 

We are seeking an experienced AI Solution Architect to lead the design and delivery of a strategic, cross-functional content extraction and interpretation platform built on Microsoft Azure. This high-impact role will support multiple business units by delivering scalable, secure, and intelligent AI capabilities, leveraging Generative AI, NLP, and Azure-native services.

,[Lead the end-to-end design and architecture of AI solutions, including models, data pipelines, and infrastructure, tailored to business needs and enterprise standards, with a focus on Microsoft Azure. , Collaborate with business stakeholders to translate requirements into scalable, production-grade AI architectures and deployment strategies. , Define and document robust AI solution architectures using Azure-native tools and services, including interfaces, data flows, and integration points. , Evaluate and recommend Azure-based AI technologies, frameworks, and services to meet performance, compliance, and scalability needs. , Design and implement secure, scalable data pipelines for training and inference of AI models, leveraging Azure AI services. , Work closely with technical teams to build, test, and operationalize AI models and algorithms aligned with best architectural practices. , Drive compliance with security and privacy standards (e.g., GDPR, internal policies) using Azure-native tools like Purview, Defender for Cloud, and Key Vault. , Provide hands-on technical leadership to multi-disciplinary project teams, mentoring architects and engineers across regions. , Stay ahead of emerging Azure AI services and trends; identify opportunities for optimization and innovation across AI initiatives. , Promote architectural governance and knowledge sharing across the AI delivery landscape. ] Requirements: AI, Microsoft Azure, NLP, Data pipelines, Security, GDPR, Cloud, Key Vault, Degree, Machine learning, Azure Data Lake, MLOps, Python, C#, PyTorch, TensorFlow, scikit-learn, Docker, Kubernetes, Communication skills, Kanban, Azure

Kategorie

artificialIntelligence

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