What are the responsibilities and job description for the Context / Retrieval Engineer (RAG Specialist) position at DeWinter Group?
Title: Context/Retrieval Engineer
Job Type: Contract
Contract Length: 12 Months
Pay Range: $50/hr – $175/hr
Start Date: ASAP
Location: Remote
About The Opportunity
Our client, a leader in AI testing and Generative AI solutions, is looking for a skilled Context/Retrieval Engineer (RAG Specialist) to join their team for a 12-month engagement. This project involves optimizing Retrieval-Augmented Generation (RAG) pipelines to improve the accuracy and relevance of AI responses. This is a high-impact role that requires a self-motivated professional who can hit the ground running and deliver results quickly.
Key Responsibilities & Deliverables
This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include:
We are looking for someone with a proven track record of successful contract engagements. The ideal candidate will have:
Job Type: Contract
Contract Length: 12 Months
Pay Range: $50/hr – $175/hr
Start Date: ASAP
Location: Remote
About The Opportunity
Our client, a leader in AI testing and Generative AI solutions, is looking for a skilled Context/Retrieval Engineer (RAG Specialist) to join their team for a 12-month engagement. This project involves optimizing Retrieval-Augmented Generation (RAG) pipelines to improve the accuracy and relevance of AI responses. This is a high-impact role that requires a self-motivated professional who can hit the ground running and deliver results quickly.
Key Responsibilities & Deliverables
This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include:
- Optimizing Retrieval-Augmented Generation (RAG) pipelines to improve the accuracy and relevance of AI responses.
- Implementing advanced "chunking" strategies and metadata tagging for enterprise documents.
- Selecting and fine-tuning embedding models to better capture domain-specific semantic meaning.
- Designing hybrid search systems combining vector similarity with traditional keyword search (BM25).
- Benchmarking various vector databases to ensure high retrieval speed and low memory overhead.
We are looking for someone with a proven track record of successful contract engagements. The ideal candidate will have:
- 3 years of experience in Information Retrieval or AI Engineering.
- Deep expertise in Vector Databases (Pinecone, Chroma, Milvus) and LangChain/LlamaIndex. This isn't a learning role—you need to be a subject matter expert.
- Demonstrated ability to work autonomously and manage your own time effectively to meet project goals.
- Experience with Python, SQL, and natural language processing (NLP) techniques.
- Strong communication skills to provide clear and concise status updates to the project team.
Salary : $175