Generative AI Engineer for Data Systems
We are seeking a Generative AI Engineer for Data Systems to lead the design and integration of AI-first tooling for modern data workflows. This role focuses on building AI-powered services such as information extraction pipelines , smart questionnaires , AI pair-programming assistants , and natural language interfaces to democratize access to data and accelerate productivity across statistical, engineering, and analytical teams. Key Responsibilities
GenAI-Enabled Data Workflows
- Design and deploy AI agents that automate steps in data pipelines (e.g., transformation, validation, documentation)
- Develop workflows that combine LLMs with data tools (SQL engines, ETL jobs, metadata catalogs)
- Integrate agentic AI frameworks into notebooks, dashboards, and API layers
- Build systems where LLMs assist in tasks such as table joining, schema inference, or chart creation
- Implement smart, AI-assisted questionnaires that adapt based on user input or metadata
- Build NLP-powered survey tools that recommend questions, auto-fill responses, or extract structured data from free text
- Enhance survey response validation and quality using LLM-based reasoning and logic
- Integrate AI coding copilots into environments used by statisticians, data scientists, and engineers
- Provide context-aware code generation, auto-documentation, and test creation inside IDEs (RStudio, VSCode, Jupyter)
- Build internal copilots for tasks such as model diagnostics, pipeline debugging, or script refactoring
- Collaborate with users to understand pain points and optimize prompt engineering strategies
- Develop conversational data tools that allow users to ask questions and get answers directly from structured and unstructured datasets
- Embed GenAI-powered search and exploration into data catalogs, dashboards, and web interfaces
- Fine-tune or prompt-engineer LLMs for safe, accurate, and explainable answers in data contexts
- Integrate multi-modal interfaces where users can speak, type, or upload to interact with datasets
Technical Skills
- 6+ years working at the intersection of data engineering , machine learning , or AI tooling
- Hands-on experience with LLMs and frameworks like LangChain , Haystack , OpenAI , or Transformers
- Proficiency in Python and experience working with data tools (SQL, pandas, dbt, Apache Airflow)
- Familiarity with frontend or UI libraries for chatbot-like or form-based applications (Streamlit, Gradio, Shiny)
- Experience integrating or fine-tuning LLMs for structured data tasks or decision support
- Understanding of prompt engineering , retrieval-augmented generation (RAG), and embedding techniques
- Comfort working with cloud APIs (OpenAI, Cohere, Anthropic) and vector databases (FAISS, Weaviate, Chroma)
- Ability to build secure, governed systems for LLM deployment in enterprise settings
- Degree in Computer Science, Data Science, Statistics, or a related field
- Experience working with or supporting data scientists and statisticians
- Familiarity with knowledge graphs, metadata standards, and semantic search
- Background in UX design for AI interfaces or conversational agents
- Awareness of ethical, legal, and safety concerns when applying GenAI to data
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