Prompt Engineer
around "Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Vector Databases, and Prompt Engineering
Richardson, TX
JD
Experience: 4-6 years in Data Engineering and AI solutions.
Strong expertise in Python, SQL, PySpack, Databricks/Spark.
Hands-on experience with Large Language Models (LLMs) such as OpenAI, Azure OpenAl, Claude, or Llama.
Build and deploy Retrieval-Augmented Generation (RAG) applications.
Develop AI Agents using LangChain, LangGcapb, CrewAI, or AutoGen frameworks.
Work with Vector Databases such as Pinecone, Odcant, Weaviate, Milvus, or ChromaDB.
Experience in Prompt Engineering, prompt optimization, and LLM orchestration.
Design document ingestion, embeddings, retrieval, and knowledge search solutions.
Develop scalable APIs and microservices for AI-powered applications.
Implement LLM evaluation, monitoring, guardrails, and responsible AI practices.
Experience with cloud platforms (Azure preferred, AWS/Google Cloud Platform acceptable).
Familiarity with Azure AI Search, Azure OpenAl, and enterprise Al frameworks.
Healthcare domain experience (Claims, Membership, Provider, Clinical) is preferred.
Strong analytical, communication, and stakeholder management skills.
Ability to work in an Agile environment and deliver enterprise-grade GenAl solutions. Based on internal AI/ML engineering role requirements emphasizing RAG pipelines, AI agents, vector databases, prompt engineering, and Python development
