Intellectica is recruiting an AI Technical Architect on behalf of a leading technology services group headquartered in Athens, Greece, operating under a hybrid working model. The selected candidate will join a high-performing Data & AI team and will play a pivotal role in designing, developing, and deploying cutting-edge AI solutions, contributing to transformative initiatives that enhance business performance, unlock new value streams, and drive innovation across diverse industries.

Key activities and responsibilities of this role include:

• Leading the end-to-end architecture and delivery of scalable, enterprise-grade AI solutions, aligning technical design with business strategy, governance, and long-term innovation objectives, while advising clients on AI strategy, modernization roadmaps, and responsible AI adoption

• Architecting and implementing end-to-end Generative and Agentic AI solutions; including agent orchestration, model selection, system integration, and agentic workflows (multi-agent systems, MCP integrations, A2A protocols) from discovery and design through deployment and scaling

• Designing cloud-native AI and Machine Learning solutions across AWS, Azure, and GCP, ensuring performance, resilience, continuous improvement, and cost-efficient scalability

• Collaborating with data engineering teams to design data platforms, vector databases, RAG architectures, feature stores, and knowledge retrieval systems

• Driving the implementation of MLOps / LLMOps pipelines, enabling continuous delivery, monitoring, governance, and lifecycle management of AI models

• Overseeing system integrations, including APIs, microservices, enterprise networks, and security frameworks

• Ensuring secure and cost-optimized architectures through API gateway integration, token and context-window budgeting, and resource utilization planning

• Providing architectural leadership in client workshops, technical assessments, and solution reviews

• Any other task that may be required from time to time

Professional experience & qualifications of a successful candidate:

• Bachelor’s degree in Computer Science, Engineering, or a related field; a Master’s degree or PhD will be considered an asset

• Minimum of 5 years of experience in Cloud Architecture, with strong expertise in at least one major cloud provider (AWS, Azure, or GCP) and hybrid enterprise environments, applying secure integration patterns

• Strong software engineering background with hands-on development in Python and/or Java, including API design, microservices, distributed systems, and Kubernetes-based container orchestration

• Solid understanding of network architecture, security models, and enterprise system integrations within cloud-native environments

• Strong experience with modern data platforms (data lakes, lakehouses, distributed storage, real-time pipelines) and Retrieval-Augmented Generation (RAG) architectures, including vector databases, embeddings, and semantic search

• Proven track record in designing and delivering Generative and Agentic AI solutions, including LLM orchestration frameworks (e.g., LangGraph, CrewAI, AutoGen, Vertex AI), multi-agent workflows, and advanced prompt engineering and model optimization techniques

• Experience establishing and guiding MLOps / LLMOps practices, enabling model deployment, monitoring, versioning, governance, and lifecycle management using cloud-native or open-source tooling, alongside DevOps and CI/CD best practices

• Exposure to AI governance, responsible AI principles, model risk management, and compliance frameworks

• Cloud certifications (AWS, Azure, GCP) are considered an asset; prior consulting or client-facing experience is highly desirable

• Fluency in Greek with professional-level English communication skills

Core competencies of a successful candidate:

• Hands-on engineering mindset with rapid prototyping capabilities and iterative solution development

• Comfortable working within a global, highly collaborative team environment

• Architectural thinking with the ability to design complex, distributed AI systems

• Proactive, dependable, and results-driven professional mindset