Overview
On Site
BASED ON EXPERIENCE
Full Time
Skills
PROMPT
LANGCHAIN
LLM
VECTOR DATABASE
Job Details
Role Overview
Design and optimize prompts for large language models to build robust AI applications. Develop LLM-powered solutions using LangChain and vector databases.
Responsibilities
- Design, test, and optimize prompts for LLMs to achieve desired outputs and behaviors
- Build and deploy LLM applications using LangChain and related frameworks
- Implement RAG (Retrieval Augmented Generation) systems with vector databases
- Develop prompt templates, chains, and agents for various use cases
- Evaluate and benchmark LLM performance across different prompting strategies
- Collaborate with engineers and product teams to integrate LLM solutions
Requirements
- Bachelor's degree in Computer Science, Engineering, Linguistics, or related field
- Proven experience in LLM prompting and prompt engineering techniques
- Strong hands-on experience with LangChain framework
- Proficiency with vector databases (Pinecone, Weaviate, ChromaDB, FAISS)
- Understanding of LLM capabilities, limitations, and best practices
- Experience with OpenAI, Anthropic, or other LLM APIs
- Proficiency in Python
Preferred
- Experience with prompt optimization techniques (few-shot, chain-of-thought, ReAct)
- Knowledge of embedding models and semantic search
- Familiarity with LLM evaluation frameworks
- Understanding of agentic workflows and tool-using LLMs
- Experience with MLOps and production deployment
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.