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Retrieval Augmented Generation Rag Jobs in Clementon, NJ

Hands-on experience designing and implementing retrieval-augmented generation (RAG) workflows * Understanding of: * LLM integration and orchestration * Embeddings and vector search * Retrieval ...

Hands-on experience designing and implementing retrieval-augmented generation (RAG) workflows * Understanding of: * LLM integration and orchestration * Embeddings and vector search * Retrieval ...

Hands-on experience designing and implementing retrieval-augmented generation (RAG) workflows * Understanding of: * LLM integration and orchestration * Embeddings and vector search * Retrieval ...

Hands-on experience designing or implementing Retrieval-Augmented Generation (RAG) solutions. * Experience with AI standards and frameworks such as Model Context Protocol (MCP), Agent2Agent (A2A ...

Hands-on experience designing or implementing Retrieval-Augmented Generation (RAG) solutions. * Experience with AI standards and frameworks such as Model Context Protocol (MCP), Agent2Agent (A2A ...

Your work will involve techniques such as fine-tuning, retrieval-augmented generation (RAG), and prompt engineering to solve meaningful business challenges. You will work closely with teams to ...

Your work will involve techniques such as fine-tuning, retrieval-augmented generation (RAG), and prompt engineering to solve meaningful business challenges. You will work closely with teams to ...

Your work will involve techniques such as fine-tuning, retrieval-augmented generation (RAG), and prompt engineering to solve meaningful business challenges. You will work closely with teams to ...

The ideal candidate will have strong expertise in LangChain, LangGraph, Retrieval-Augmented Generation (RAG), agentic AI workflows, and scalable cloud-native architectures. This role involves ...

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Integrate and optimize vector databases for semantic search and retrieval-augmented generation (RAG) applications. * Collaborate closely with data engineers and business stakeholders to translate ...

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Retrieval Augmented Generation Rag information

See Clementon, NJ salary details

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How much do retrieval augmented generation rag jobs pay per hour?

As of Jul 26, 2026, the average hourly pay for retrieval augmented generation rag in Clementon, NJ is $20.65, according to ZipRecruiter salary data. Most workers in this role earn between $17.64 and $21.59 per hour, depending on experience, location, and employer.
What cities near Clementon, NJ are hiring for Retrieval Augmented Generation Rag jobs? Cities near Clementon, NJ with the most Retrieval Augmented Generation Rag job openings:
Infographic showing various Retrieval Augmented Generation Rag job openings in Clementon, NJ as of July 2026, with employment types broken down into 100% Full Time. Highlights an 49% In-person, and 51% Remote job distribution, with an average salary of $42,961 per year, or $20.7 per hour.
Software Developer / Engineer - Philadelphia, PA (Locals Only)

Software Developer / Engineer - Philadelphia, PA (Locals Only)

Apetan Consulting

Philadelphia, PA • On-site

Other

Posted 3 days ago


Job description

Software Developer / Engineer
Location: Philadelphia, PA 
Work Schedule: Hybrid 3 days on site, 2 remote


Position Overview

We are seeking a Software Developer / Engineer to help design and implement an on-premises Large Language Model (LLM) platform with Retrieval-Augmented Generation (RAG) capabilities. This role will focus on deploying open-source AI models, integrating vector databases, and building secure, enterprise-grade AI solutions in a private environment.

This is an excellent opportunity for a developer with hands-on experience in modern AI technologies who enjoys building scalable, high-performance systems.

Responsibilities

  • Deploy and optimize open-source large language models (LLMs) such as Meta Llama 3 and Mistral/Mixtral in on-premises or private environments.
  • Develop Python-based applications for LLM inference, prompt engineering, and model integration.
  • Optimize CPU-based model inference through quantization and performance tuning.
  • Design and implement Retrieval-Augmented Generation (RAG) (RAG) pipelines.
  • Configure and manage open-source vector databases such as Qdrant, Chroma, Milvus, or pgvector.
  • Generate and manage embeddings while implementing metadata filtering strategies.
  • Support enterprise security requirements, including air-gapped deployments, access controls, data privacy, and audit logging.
  • Produce technical documentation, deployment guidance, and knowledge transfer materials for internal teams.
  • Build a working prototype integrating an LLM, vector database, and RAG architecture.

Required Qualifications

  • Professional experience deploying open-source LLMs (e.g., Meta Llama 3, Mistral/Mixtral) in on-premises or private environments.
  • Strong Python development experience.
  • Hands-on experience with LLM inference, prompt engineering, and AI application integration.
  • Experience optimizing CPU-based inference through model quantization and performance tuning.
  • Experience with vector databases such as Qdrant, Chroma, Milvus, or pgvector.
  • Proven experience implementing Retrieval-Augmented Generation (RAG) solutions.
  • Understanding of enterprise security, data privacy, air-gapped environments, access controls, and audit logging.

Preferred Qualifications

  • Experience with LangChain or LlamaIndex.
  • Familiarity with Docker and Kubernetes.
  • Experience with inference frameworks such as vLLM, llama.cpp, or Hugging Face Transformers.
  • Experience with Rust, Go, or C++.
  • Previous experience working in enterprise or regulated environments.

Deliverables

  • Reference architecture and deployment guidance.
  • Working prototype integrating an LLM, vector database, and RAG solution.
  • Technical documentation and knowledge transfer to internal teams.