Back
Mid-level AI role, metro Bangalore location, popular title, and broad required skills increase applicant competition.
AI and data engineering skills transfer across industries but require specific cloud, Databricks and MLOps experience.
Explicit 2–4 years plus multiple mandatory technologies (Databricks, Azure, LLMs, Power Automate) make filters strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and maintain scalable data pipelines and AI-driven automation workflows using Python and Databricks.
Integrate and operationalize Large Language Models (LLMs) such as OpenAI / Azure OpenAI including prompt engineering and API usage within enterprise data and AI workflows.
Lead technical discussions, mentor junior team members, and participate in architecture decisions for AI and data engineering solutions on Azure cloud platform.
2–4 years of professional experience in Python development focused on data engineering or AI projects.
Hands-on experience with Databricks for data processing and machine learning workflows.
Strong proficiency in Azure cloud services including Data Lake, Azure Functions, and workflow automation tools like Power Automate.
Practical experience with Large Language Models (LLMs), prompt engineering, API integrations, and familiarity with MLOps and deploying AI models in production.
Experienced in building end-to-end AI workflows combining data engineering, automation, and generative AI capabilities in enterprise environments.
Comfortable operating in cloud-native environments, particularly with Azure services and advanced data platforms like Databricks.
Capable of translating business requirements into scalable technical solutions and leading technical discussions including mentoring junior engineers.