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Popular mid-level AI role with broad required skills at a known employer in a metro increases competition.
ML/AI and cloud data engineering skills transfer across industries, though GenAI/MLOps needs some domain context.
Mandatory seven years plus specific cloud, Databricks, PySpark, GenAI and production automation requirements increase filtering.
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Develop and maintain automation solutions across analytics programs to improve operational efficiency.
Build and support Power BI dashboards, semantic models, KPI scorecards, and executive reporting.
Collaborate with business units to identify AI use cases, support GenAI initiatives, and deliver intelligent knowledge discovery capabilities.
Minimum 7 years of hands-on experience in Data Analysis, Automation, and Cloud-native development.
Strong programming skills in Python, PySpark, Databricks, BigQuery/Redshift, SQL, and Python libraries such as NumPy, Pandas, and Matplotlib.
Experience delivering cloud native solutions and automations in production environments.
Notice Period: Not explicitly mentioned in the JD.
Experienced in designing and building APIs/services using FastAPI or Flask frameworks for production use.
Familiarity with generative AI technologies and frameworks, including Retrieval-Augmented Generation (RAG) is preferred.
Knowledge of MLOps principles, including model versioning, automated evaluation, and CI/CD processes, enhances fit for the role.