Senior AI & Data Engineer

• Design, develop, and optimize ETL/ELT pipelines to ingest structured and unstructured data from multiple sources.
• Build and maintain data lakes, data warehouses, and databases to support analytics and business intelligence.
• Ensure data quality, reliability, and consistency across different environments.
• Implement and optimize SQL and NoSQL databases for performance and scalability.
• Collaborate with cross-functional teams to integrate data from various business systems.
• Build and deploy LLM-powered applications and GenAI features
• Set up and maintain ML training pipelines and experiment tracking
• Own MLOps workflows — model packaging, versioning, monitoring, and deployment
• Prepare and process training datasets for ML models

Qualifications

• Strong proficiency in SQL and hands-on experience with relational databases.
• Solid understanding of data modeling, warehousing concepts, and performance tuning.
• Hands-on experience with ETL tools (e.g., Talend, Informatica, dbt, Airflow, etc.).
• Strong problem-solving skills with the ability to work in an agile, fast-paced environment.
• Experience with version control (e.g., Git) and workflow orchestration tools (e.g., Airflow, Prefect, Luigi) is a plus.

Tech stack & Knowledge

• Vector Databases — Pinecone, Weaviate, ChromaDB
• LLM / GenAI Tools — LangChain, LlamaIndex, OpenAI APIs
• ML Training & Experiment Tracking — MLflow, Weights & Biases, Hugging Face
• RAG (Retrieval-Augmented Generation) concepts and Prompt engineering basics