AI/RAG Engineer

Shree Narayani Networking Solutions • Dallas, TX

1d

About The Position

We are seeking an AI/RAG Engineer, specifically a full-stack GenAI application engineer who has experience shipping a RAG product end-to-end, not just calling an LLM API. This role requires hands-on experience with the full RAG pipeline, including chunking strategy, embedding model selection, retrieval tuning, and reranking/summarization, with an understanding of the trade-offs at each stage. Strong application layer skills are essential, including FastAPI, JWT/auth, API Gateway patterns, MongoDB/Redis, and ideally some Angular/React exposure. Experience in semantic search and data pipelines, including building search/retrieval systems (even pre-LLM), is highly valued. This is an opportunity for a well-rounded builder with backend, data pipeline, and some frontend awareness. A good fit would be a product-minded backend engineer who has spent the last 1-2 years specifically in applied GenAI/RAG, ideally in a team shipping to real users rather than in research or prototyping.

Requirements

• Shipped a RAG product end-to-end
• Experience with RAG, semantic search, and embeddings
• Product shipping experience
• Hands-on with the full RAG pipeline (chunking strategy, embedding model selection, retrieval tuning, reranking, summarization)
• Strong application layer skills: FastAPI, JWT/auth, API Gateway patterns
• Experience with MongoDB/Redis
• Experience building search/retrieval systems
• Product-minded backend engineering experience
• 1-2 years of experience in applied GenAI/RAG

Nice To Haves

• Angular/React exposure

Responsibilities

• Hands-on with the full RAG pipeline: chunking strategy, embedding model selection, retrieval tuning, reranking, summarization
• Understanding and discussing trade-offs at each stage of the RAG pipeline
• Developing the application layer, including FastAPI, JWT/auth, and API Gateway patterns
• Working with databases like MongoDB/Redis
• Potentially contributing to frontend development with Angular/React exposure
• Building and optimizing semantic search and data pipelines
• Shipping RAG products end-to-end to real users

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed