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

- Strong 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