What are the responsibilities and job description for the Senior Data Engineer with AI position at Rockwoods Inc?
Title: Senior Data Engineer with AI
Location: Remote
US Citizens only.
Job Summary
Rockwoods is seeking a Senior Data Engineer with AI with a specialized focus on the intersection of Data Infrastructure and AI. The ideal candidate doesn't just build pipelines; they build the backbone for intelligent systems. You will be responsible for architecting large-scale data environments that fuel LLM integrations and production-grade AI models.
Key Responsibilities
- Design, build, and scale production-grade data pipelines specifically optimized for AI workflows, including data ingestion for LLM fine-tuning and RAG (Retrieval-Augmented Generation) patterns.
- Seamlessly integrate AI APIs (OpenAI, Hugging Face, Anthropic) into existing data transformation and downstream usage layers for real-world projects.
- Lead the cleaning, transformation, and feature engineering of large-scale datasets to ensure they are structured specifically for high-performance AI model training and inference.
- Deploy and support AI solutions in production environments, managing the end-to-end lifecycle including monitoring, scaling, and resolving real data issues.
- Develop and maintain dbt-based transformation layers and optimize Snowflake performance for both analytical and AI-driven workloads.
- Implement robust API and event-driven ingestion pipelines with a focus on data quality, validation, and reliability across the entire AI data lifecycle.
What We’re Looking For
- 6–10 years of hands-on data engineering experience with deep expertise in Python, dbt, and Snowflake.
- Proven track record of integrating LLM/AI APIs into complex data pipelines for data ingestion, transformation, or downstream usage.
- Demonstrated ability to deploy and support AI solutions in production, including active monitoring and scaling of models and data flows.
- Advanced experience in preparing and structuring large-scale data (cleaning, transformation, and feature engineering) specifically for AI model usage.
- Strong mastery of Airflow or similar orchestration tools to manage complex AI data workflows.
- Solid understanding of data modeling and a proven track record of building production-grade pipelines that handle real-world data issues.
Why Rockwoods
- Strong pipeline of modern data platform work
- Direct exposure to real client systems
- Opportunity to grow into architecture roles
- Execution-focused culture-less process, more impact