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Job Description As a key technical contributor, you will design, build, and implement AI models and intelligent applications as part of Avanade’s Data & AI portfolio. You will work hands-on with Microsoft Azure AI services, machine learning frameworks, and modern engineering practices to develop solutions that address real business problems. While the AI Architect focuses on high-level solution design and pre-sales support, your role focuses on delivering the technical foundations: implementing models, supporting architecture with detailed designs, and ensuring the AI components are robust, scalable, and production-ready. You will collaborate closely with business stakeholders, Solution Architects, Data Engineers, and Data Scientists to ensure that what we build actually works — and delivers value. Together, we do what matters. Key Responsibilities: Translate business and functional requirements into detailed AI solution components and technical tasks. Analyze current client processes, data sources, and system architecture to identify opportunities for AI-driven enhancements. Develop machine learning and AI models using Python, Azure Machine Learning, Azure Cognitive Services, and modern ML frameworks. Build and optimize end-to-end pipelines for data preparation, feature engineering, training, evaluation, and deployment. Support Solution Architects by contributing detailed technical insight, assumptions, and effort estimation for AI-related workstreams. Identify risks, constraints, and dependencies within AI development cycles and communicate these clearly to project leaders. Implement best practices for model versioning, testing, monitoring, and lifecycle management. Participate in code reviews, solution validation, and technical documentation efforts to ensure quality and maintainability. Collaborate cross-functionally with data engineers, product owners, business analysts, and other technical specialists throughout the delivery lifecycle. Mentor junior team members by sharing technical expertise and supporting their development through hands-on guidance. Job Qualifications Strong programming skills with Python and familiarity with ML/AI libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Experience working with Azure AI services such as Azure Machine Learning, Cognitive Services, Azure OpenAI, or Data Lake technologies. Understanding of the data science lifecycle, including experimentation, model development, validation, and deployment. Experience building prototypes, proofs of concept, or MVPs to demonstrate AI capabilities and validate solutions. Ability to evaluate datasets, determine appropriate modeling techniques, and justify technical decisions. Strong analytical and problem-solving skills with attention to detail and quality. Experience working within multi-disciplinary teams and communicating technical concepts in a clear, business-relevant manner. Familiarity with containerization (Docker), CI/CD, or MLOps concepts is a plus. A passion for staying current with developments in AI, ML, and cloud technologies.