Key Responsibilities
Design, develop, and deploy AI/ML and Generative AI solutions using the Databricks platform.
Build and implement LLM-powered applications, including Retrieval-Augmented Generation (RAG) solutions.
Develop scalable data processing and AI pipelines using PySpark, Python, and Spark SQL.
Utilize Databricks Mosaic AI capabilities for developing and deploying AI applications.
Implement Vector Search, embedding models, and semantic search capabilities.
Integrate Large Language Models (LLMs) with enterprise data sources and applications.
Develop and optimize prompt engineering strategies for LLM-based applications.
Use MLflow for model tracking, experimentation, evaluation, and deployment.
Implement MLOps practices for model deployment, monitoring, and lifecycle management.
Work closely with clients and stakeholders to understand requirements and provide technical solutions.




Participate in client discussions, technical design sessions, and solution demonstrations.
Troubleshoot and optimize AI application performance, scalability, and reliability.

Mandatory Skills
Robust hands-on experience with Databricks.
Experience in Python programming and PySpark.
Practical experience in AI/ML or Generative AI development.
Hands-on experience with Large Language Models (LLMs).
Experience in developing RAG-based applications.
Knowledge of embeddings, vector databases, and semantic search.
Experience with MLflow or equivalent model lifecycle management tools.
Experience in developing and deploying AI solutions in cloud environments.
Robust analytical, problem-solving, and communication skills.

📌 Databricks Ai Engineer Bengaluru
🏢 Kiya.ai
📍 Bengaluru