Job Description

Python, SQL, ETL/ELT, Data Modeling, Data Quality, Cloud-native Development, API Integration, Data Engineering, ETL, Document Processing, Workflow design, knowledge of LLM development, RAG, Prompt Engineering, AI Coding Assistants Advanced Skills: RAG Data Pipelines, LLM Data Integration, AI Service Integration, Scalable AI Deployments, Agent Orchestration, Tool Calling, LangGraph, LangChain

Design and develop GenAI applications using Python and enterprise LLM platforms. 2. Build scalable data pipelines for structured and unstructured data processing. 3. Implement Retrieval-Augmented Generation (RAG) systems and vector-based search solutions. 4. Integrate LLMs with enterprise applications through APIs and workflows. 5. Develop cloud-native AI services on AWS, Azure, GCP, Databricks (DBRX), or Snowflake. 6. Create agent-based solutions using LangChain and LangGraph. 7. Ensure data quality, governance, and security compliance across AI workflows. 8. Optimize performance, scalability, and reliability of AI solutions.
1+ years of experience with Hugging Face, LangChain, OpenAI, Anthropic, Gemini, or open-source LLMs. 2. Familiarity with knowledge graphs and semantic search. 3. Experience building production-grade GenAI solutions

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