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engaging with business stakeholders, mentoring teams, and driving AI innovation across data platforms.\n\nTotal Experience : 8 - 18 years\n\nRequired Skills :\n\nAI & Machine Learning :\n\n- Artificial Intelligence (AI)\n\n- Machine Learning (ML)\n\n- Generative AI\n\n- Large Language Models (LLMs)\n\n- Retrieval Augmented Generation (RAG)\n\n- NLP (Natural Language Processing)\n\n- Prompt Engineering\n\n- AI Agents & Autonomous Workflows\n\nData Engineering :\n\n- ETL/ELT Architecture\n\n- Databricks\n\n- Snowflake\n\n- Data Warehousing\n\n- Data Lakehouse Architecture\n\n- Apache Spark\n\n- Data Governance\n\n- Data Quality Frameworks\n\nProgramming :\n\n- Python\n\n- SQL\n\n- PySpark\n\n- REST APIs\n\n- Microservices Architecture\n\nCloud Platforms :\n\n- Azure / AWS / GCP\n\n- Azure OpenAI / OpenAI Services\n\n- Cloud-native AI Solutions\n\nMandatory Complex Project Experience :\n\nThe candidate should have successfully designed or delivered one or more of the following 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end-to-end design of AI-powered enterprise solutions.\n\n- Drive implementation of GenAI, RAG, NLP, and ML initiatives.\n\n- Collaborate with business, data, and engineering teams.\n\n- Build scalable AI platforms and reusable frameworks.\n\n- Establish AI governance, security, and responsible AI practices.\n\n- Mentor architects, leads, and development teams.\n\n- Conduct architecture reviews and technology evaluations.\n\n- Engage with clients and provide technical leadership.\n\nPreferred Qualifications :\n\n- Bachelor's/Master's in Computer Science, AI, Data Science, or related field.\n\n- Certifications in Azure AI, AWS AI/ML, Databricks, Snowflake, or Cloud technologies.\n\n- Experience leading enterprise-scale AI transformation programs.\n\n- Strong stakeholder management and client-facing experience.\n\nSkills\nArtificial Intelligence, Machine Learning, Generative AI, NLP, Prompt Engineering, ETL, Python, PySpark, Databricks, Data Warehousing, 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