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Strong brand and metro increase competition, but senior niche role reduces it.
Highly specialized enterprise data and agentic AI experience reduces cross-industry transferability.
Explicit 12+ years and many mandatory technical AI, data, and platform skills imply strict filters.
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Design, develop, and maintain scalable ETL processes and data pipelines using Python and related libraries to handle large volume data.
Implement and optimize AI and machine learning solutions integrating large language models and AI frameworks within enterprise systems.
Ensure operational stability, develop robust APIs for AI services, and apply software development best practices including CI/CD, version control, and testing.
12+ years of experience in data domain and large volume data handling.
Expert-level proficiency in Python and relevant AI/ML frameworks (TensorFlow, PyTorch, Scikit-Learn, etc.).
Strong knowledge of database technologies such as Oracle, Postgres, or MongoDB.
Experience with AI methodologies (chunking, embedding, prompt engineering) and large language models (ChatGPT, Claude, Gemini, Llama).
Experienced individual contributor with deep expertise in designing and implementing scalable AI-centric data engineering solutions.
Strong strategic understanding of AI system design, including agentic AI and Model Context Protocol integration.
Proficient in developing and managing microservices architectures with API-first design and event-driven patterns, leveraging containerization (Docker, Openshift).