AI Solution Architect

Why Keyrus, Why Now! Keyrus is an international group of 2,800 consultants and experts across 28 countries , built on a single conviction: AI does not transform businesses. Architected intelligence does. For more than 30 years, we have been building the data foundations that make intelligent systems work — designing the Operating System of the intelligent enterprise, where intelligence is embedded into the core of business processes to create sustainable value: we operationalise intelligence . AI does not replace humans. It repositions us to a place no system can follow: understanding, deciding, designing, and creating. At Keyrus, you will not just develop skills - you will develop judgment. Your expertise sharpens with every system you architect, every client challenge you solve, every deployment that compounds on the last. Over time, you grow into one of the rarest professionals of the intelligence era: someone who bridges data, AI, and human decision-making at scale, across industries and geographies. This is not a role you fill. It is a discipline you master and a story you help write to become a Keyrus Architect of Intelligence . Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two. 🚀 What You'll Architect As an AI Solution Architect • Design end-to-end AI solutions, including Generative AI applications, LLM-powered workflows, intelligent agents, RAG solutions, virtual assistants, and intelligent automation. • Translate business requirements and use cases into practical technical architectures, identifying appropriate AI models, services, data sources, integrations, and infrastructure. • Collaborate with AI Engineers, Software Engineers, Data Scientists, and Data Engineers to move solutions from concept and prototype to production. • Develop and validate prototypes and proof-of-concepts to evaluate technical feasibility, business value, and architectural approaches. • Contribute to the creation of modular and reusable AI components, services, APIs, and architectural patterns that can support multiple business use cases. • Design and integrate AI solutions with enterprise applications, APIs, data platforms, vector databases, and cloud services. • Contribute to the design of agentic AI solutions, including tool integration, orchestration, memory, RAG, and human-in-the-loop patterns. • Help evaluate AI technologies, frameworks, models, and platforms and recommend appropriate options based on solution requirements, performance, scalability, security, and cost. • Collaborate with Enterprise Architecture, Cybersecurity, Legal, Privacy, and Quality teams. • Incorporate Responsible AI, security-by-design, privacy-by-design, and compliance-by-design principles into AI solutions. • Support the implementation of monitoring, evaluation, observability, and MLOps/LLMOps practices for production AI solutions. • Document solution architectures, technical decisions, integration patterns, and implementation guidance. • Stay current with emerging developments in Generative AI, agentic AI, cloud AI platforms, and enterprise AI architecture, and help identify opportunities to apply them to meaningful business challenges. 🧠 Who You Are You are a technically minded professional who combines architectural thinking with hands-on AI development. You enjoy understanding complex business challenges, exploring emerging technologies, and translating ideas into practical solutions that can operate reliably at enterprise scale. You can move between technical discussions and business conversations, evaluate different approaches, and explain the trade-offs behind your decisions. You understand that successful AI solutions require more than innovative models: they must also be scalable, secure, maintainable, cost-effective, and responsible. You are curious, analytical, collaborative, and comfortable working with multidisciplinary teams in a dynamic, globally connected environment. 🛠️ What You Bring Qualifications / Certifications • Bachelor's degree in Computer Science, Software Engineering, Systems Engineering, Data Science, Artificial Intelligence, or a related technical field, or equivalent relevant experience. • At least 3 years of professional experience in software engineering, solution engineering, cloud engineering, data/AI engineering, solution architecture, or related technical roles. • Hands-on experience designing or developing AI/ML or Generative AI solutions. • Practical understanding of Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, vector search, and AI agents. • Experience with at least one major cloud platform, preferably Microsoft Azure and/or AWS. • Experience designing or integrating APIs, microservices, and cloud-native applications. • Programming experience, preferably in Python, with the ability to build prototypes and validate architectural decisions. • Understanding of software engineering practices, including version control, testing, CI/CD, and modern DevOps practices. • Awareness of AI security, data privacy, Responsible AI, and governance considerations for enterprise AI solutions. • Strong analytical and problem-solving skills, including the ability to assess alternative technical approaches and their trade-offs. • Excellent communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders. • Ability to collaborate effectively with multidisciplinary and geographically distributed teams. • Fluent English, both written and spoken , to participate confidently in technical discussions, presentations, and meetings with global teams. ⭐ Nice-to-haves • Experience with enterprise Generative AI platforms such as Azure AI Foundry, Azure OpenAI, AWS Bedrock, or similar technologies. • Hands-on experience with AI orchestration and agent frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, or equ