n\u25cf Translate business needs into secure and scalable solution designs, prototypes, and production implementations with defined owners, success metrics, and measurable outcomes.\n \n\u25cf Build AI-enabled applications, agents, retrieval-augmented generation solutions, integrations, APIs, and automated workflows across approved Azure, AWS, SaaS, and hybrid environments.\n \n\u25cf Develop reusable architecture patterns, reference implementations, evaluation methods, and CI/CD controls that accelerate delivery across teams.\n \n\u25cf Evaluate emerging AI models, platforms, and agent frameworks for enterprise applicability, security, supportability, cost, and production readiness.\n \nEnablement & Technical Guidance\n \n\u25cf Provide hands-on technical guidance and enablement to internal engineering teams on AI tools, frameworks, and best practices.\n \nQualifikationen\n \nQUALIFICATIONS\n \nRequired Qualifications\n \n\u25cf Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field, or an equivalent combination of education and experience.\n \n\u25cf Nine or more years of software, platform, cloud, integration, or solution engineering experience, including recent hands-on delivery of AI-enabled solutions.\n \n\u25cf Practical experience with large language models, generative AI, RAG, prompt and evaluation techniques, and cloud AI services on Azure, AWS, or Google Cloud.\n \n\u25cf Strong programming skills in Java, Python, and/or TypeScript/JavaScript.\n \n\u25cf Experience with APIs, microservices, identity and access controls, CI/CD, containers, observability, and enterprise integration patterns.\n \n\u25cf Strong analytical, problem-solving, communication, and stakeholder-management skills.\n \nPreferred Qualifications\n\n Experience in a forward-deployed, embedded, consulting, enablement, or customer-facing engineering role.\n