AI Implementation Expert

Responsibilities •Engage with stakeholders to identify AI-driven automation and optimization opportunities. •Translate business problems into AI use cases with measurable business outcomes and ROI. •Design and implement AI solutions using tools such as Azure OpenAI, ChatGPT, Microsoft Copilot, Power Automate, and Microsoft Fabric. •Build AI copilots, conversational agents, and RAG-based solutions integrated with enterprise workflows. •Develop and deploy ML models for use cases such as forecasting, anomaly detection, and classification. •Integrate AI solutions with APIs, enterprise systems, and existing data platforms. •Implement monitoring, prompt tuning, retraining, and continuous improvement practices. •Ensure secure, ethical, and compliant AI implementation aligned with governance standards. •Support user adoption, AI literacy, documentation, and reusable AI solution patterns. Requirements •Strong experience with Generative AI tools and frameworks such as ChatGPT, Azure OpenAI, Copilot Studio, and Power Automate. •Hands-on experience designing and deploying AI Agents, copilots, or AI-powered automation solutions. •Proficiency in Python, SQL, REST APIs, and ML/data science libraries such as pandas and scikit-learn. •Familiarity with Microsoft Fabric, Power BI, Azure ML, or similar data platforms. •Good understanding of ML lifecycle concepts including data preparation, model training, evaluation, and deployment. •Strong analytical, problem-solving, and stakeholder communication skills. •Ability to conduct workshops, gather business requirements, and explain technical solutions in business terms. •Experience in AI consulting, automation, analytics, or AI product implementation is preferred. •Exposure to manufacturing, supply chain, or operational domains is an added advantage.