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Tier-1 brand, metro location, mid-level generalist AI/data role with broad skills drives high applicant competition.
ML and data engineering skills are transferable across industries, though enterprise analytics experience moderately limits fit.
Explicit 5+ years plus mandatory Python, LLM, and data engineering stack creates strict shortlisting filters.
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Design, develop, and deploy production-grade AI applications leveraging Large Language Models (LLMs) and advanced AI workflows including multi-agent architectures and prompt engineering.
Build scalable ETL/ELT pipelines, semantic data layers, and manage data quality for diverse enterprise data types including structured, semi-structured, and geospatial datasets.
Develop conversational analytics platforms, interactive dashboards, and enterprise BI solutions collaborating with cross-functional teams to enable intelligent decision-making.
Minimum 5+ years of experience in Artificial Intelligence, Machine Learning, Data Engineering, Analytics, or related disciplines.
3+ years hands-on experience developing production-grade applications using Python.
Experience working with structured, semi-structured, and geospatial datasets.
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Information Systems, or a related field.
Experienced in building enterprise AI-powered analytics platforms integrating LLMs and agentic AI systems.
Proficient in designing and optimizing scalable data engineering pipelines and semantic data models for large enterprise datasets.
Skilled at collaborating across product, software, data engineering, and business teams to deliver secure, reliable, production-ready AI and analytics solutions.