3 months ago
Athens, GreeceSenior
Responsibilities
- Design and implement AI/ML, LLM, RAG, AI agent, and intelligent automation solutions using Microsoft Azure, Microsoft Fabric, Azure AI services, Azure OpenAI, Copilot Studio, and related Microsoft technologies.
- Contribute to AI solution architecture, data integration patterns, model deployment approaches, enterprise automation workflows, and scalable technical designs.
- Partner with business and IT stakeholders to identify needs, process pain points, requirements, risks, dependencies, success criteria, and business value.
- Build AI-powered applications, APIs, prototypes, predictive models, intelligent workflows, data pipelines, model-serving components, and production-ready services.
- Integrate AI/ML solutions with Azure services, Microsoft Fabric, Azure OpenAI, Copilot Studio, enterprise data platforms, APIs, and business applications.
- Research and recommend practical approaches for AI/ML, LLM, RAG, AI agent, automation, MLOps, and LLMOps use cases.
- Participate in code reviews, design reviews, and technical quality checks covering coding principles, security, documentation, reusable patterns, and maintainability.
- Create and maintain technical documentation, solution diagrams, requirements summaries, implementation notes, architecture records, and reusable templates.
- Drive continuous improvement in AI engineering practices, solution patterns, documentation, governance, and maintainability.
Requirements
- At least 4 years of professional experience in AI/ML, data science, applied machine learning, AI engineering, or a related technical field.
- Hands-on experience designing, developing, deploying, and maintaining enterprise or business AI/ML solutions.
- Strong practical experience with Microsoft Azure, including Azure AI services, Azure Machine Learning, Azure OpenAI, deployment patterns, integration approaches, and security-aware design.
- Strong working knowledge of Microsoft Fabric or similar tools for data integration, analytics, data engineering, data science enablement, and AI/ML delivery.
- Experience contributing to AI/ML solution architecture in an Azure- and Fabric-oriented enterprise environment.
- Experience with LLM applications, RAG architectures, conversational AI, AI agents, or intelligent automation.
- Experience building backend services, APIs, data pipelines, model-serving components, or AI-powered applications using Python and relevant frameworks.
- Strong understanding of AI/ML concepts, algorithms, model development, deployment, lifecycle management, and evaluation.
- Ability to translate business problems into structured technical solutions and scalable implementation designs, including requirements clarification, stakeholder alignment, value assessment, and solution scoping.
- Strong English verbal and written communication skills and the ability to explain technical concepts to business stakeholders.
- Bachelor's degree in computer science, engineering, data science, artificial intelligence, mathematics, statistics, or another STEM discipline.
- A master's degree or higher in data science, machine learning, artificial intelligence, computer science, engineering, or a related field is a strong plus.
- Experience with Azure architecture, Azure Data Factory, Azure Functions, Azure Container Apps, Azure API Management, Key Vault, Monitor, and security services is an asset.
- Advanced experience with Microsoft Fabric workloads, including Lakehouse, Warehouse, Data Factory, Data Engineering, Data Science, Power BI, OneLake, and governance capabilities is an asset.
- Experience designing enterprise RAG architectures using Azure OpenAI, embeddings, vector databases, semantic search, secure retrieval, and access-controlled knowledge sources is an asset.
- Experience with Microsoft Copilot Studio, Power Platform, LLMs, OpenAI models, Spark, Databricks, MLOps, LLMOps, CI/CD, model monitoring, prompt/model evaluation, and production AI governance is an asset.
- Experience producing solution architecture documentation, technical design documents, architecture decision records, diagrams, implementation roadmaps, or reusable technical templates is an asset.
- Experience working in global, cross-functional, matrixed organizations is an asset.
- Strong collaboration, ownership, accountability, curiosity, and commitment to continuous learning are expected.
Benefits
- Up to 10% travel is required, including some international travel as needed.
- Flexible work hours may be required to accommodate time-zone differences and appropriate meeting times.
Tech Stack
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