Description

You will design, build, and deploy intelligent, scalable GenAI solutions integrated into enterprise data and analytics platforms.

This role is hybrid.

Responsibilities

• Design and implement end-to-end Generative AI solutions on Databricks, leveraging Unity Catalog, MLflow, Delta Lake, and Vector Search.
• Architect LLM-based multi-agent frameworks for intelligent automation, chatbot systems, and document reasoning tasks.
• Fine-tune and evaluate LLMs and domain-specific NLP models for tasks like NER, Risk Assessment, and Question Answering.
• Build and maintain feature stores and embeddings stores using Databricks or Snowflake.
• Develop reusable ML pipelines using Databricks Repos, MLflow, and Feature Store, automating deployment and retraining.

Required Skills

• 8+ years of professional experience in AI/ML engineering.
• Strong background in Machine Learning, NLP, and LLMs (Transformers, RAG, embedding models).
• Proven experience fine-tuning models using Hugging Face, LangChain, LlamaIndex, or OpenAI API.
• Expertise in Databricks, including Delta Lake, MLflow, Unity Catalog, and Vector Search.
• Proficiency in Python, SQL, PySpark, and Databricks Notebooks.
• Familiarity with Azure Databricks and Azure OpenAI integration.
• Experience building modular codebases and deploying APIs using FastAPI or REST.
• Hands-on experience with MLflow tracking, model registry, and experiment management.
• Bachelor's degree required.

Preferred Skills

• Experience with Snowflake for feature and embeddings stores.

Key Skills

Education

Bachelor's degree