Job Title

We are seeking a motivated AI & Data Engineer with 23 years of experience to join our innovative team. This role sits at the intersection of data engineering, cloud analytics, and applied AI, where you''ll design scalable data pipelines while also enabling LLM-powered applications and machine learning workflows. You will collaborate closely with data scientists, ML engineers, and product teams to transform raw data into intelligent insights, AI-driven features, and production-ready LLM solutions. Key Responsibilities Data Engineering & Analytics Design, build, and optimize ETL pipelines using Apache Airflow Build and maintain Snowflake data warehouses for scalable ingestion, transformation, and analytics Develop data workflows for structured and semi-structured data using AWS services Integrate data from APIs, databases, and cloud storage using Python Implement data quality checks, monitoring, and validation frameworks Design and document data models to support analytics and ML workflows Document pipeline architectures, schemas, and best practices AI, ML & LLM Enablement Collaborate with data scientists and ML engineers to prepare datasets for AI/ML training and inference Support LLM-powered applications, including: Prompt engineering and optimization Fine-tuning LLMs (instruction tuning, domain adaptation) Managing embeddings, vector databases, and retrieval pipelines Build data pipelines to support RAG (Retrieval-Augmented Generation) workflows Develop Streamlit applications for data exploration, AI demos, and internal tools Assist in deploying and monitoring AI/ML pipelines in production environments Required Qualifications 23 years of professional experience in Data Engineering, AI Engineering, or a related role Strong hands-on experience with Apache Airflow Practical experience with AWS services (S3, Lambda, Glue, EC2, or similar) Experience working with Snowflake for data warehousing Strong Python skills for data processing, automation, and API integration Experience building data apps or dashboards using Streamlit Solid understanding of data modeling and ETL design Working knowledge of AI/ML workflows, especially data preparation Familiarity with LLMs, including: Prompt engineering Fine-tuning or adapting LLMs Working with embeddings and vector stores Bachelor''s degree in Computer Science, Data Engineering, AI, or equivalent experience Preferred Qualifications Advanced experience with AWS data and ML services Deep expertise in Snowflake performance tuning and optimization Experience building complex Streamlit applications Advanced Python skills for large-scale data wrangling Experience with LLM fine-tuning, evaluation, and deployment Familiarity with LangChain, LlamaIndex, or similar LLM frameworks Knowledge of Airflow best practices for scalable pipeline design Experience with AI/ML model deployment and monitoring