> Markdown version of [/jobs/ext/1454057-sharepoint-consultant-only-locals](https://www.wearedevelopers.com/jobs/ext/1454057-sharepoint-consultant-only-locals). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Sharepoint consultant(Only Locals)

- **Company:** Real Soft Inc.
- **Location:** Philadelphia, PA, United States
- **Experience:** Experienced
- **Salary:** $104,000.0 - $124,800.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, C++ (Programming Language), Python (Programming Language), Metadata, Open Source Technology, Performance Tuning, Microsoft SharePoint, Data Logging, Large Language Models, Generative AI, Backend, Optimization Algorithms, HuggingFace, Docker
- **Published:** July 26, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=474ad752405a226c

## About the Role

We are seeking a mid-level Software Developer/Engineer with hands-on experience in deploying on-premise LLM solutions and vector databases. The ideal candidate will have strong expertise in Python, RAG pipelines, and enterprise-grade AI system implementation within secure environments., * Strong experience with Python for AI/ML and backend development

 * Hands-on experience with open-source LLM deployment (Llama 3, Mistral, Mixtral)
 * Experience with CPU-based inference and optimization techniques
 * Practical experience with vector databases (Qdrant, Chroma, Milvus, pgvector)
 * Proven experience building RAG pipelines
 * Knowledge of embeddings, similarity search, and metadata filtering
 * Understanding of enterprise security, data privacy, and air-gapped environments

Preferred Qualifications

 * Experience with LangChain or LlamaIndex
 * Familiarity with Docker and Kubernetes
 * Exposure to Rust, Go, or C++ for high-performance systems
 * Experience with LLM inference frameworks (vLLM, llama.cpp, Hugging Face Transformers)
 * Prior experience in regulated or enterprise environments

Deliverables

 * End-to-end reference architecture for LLM + vector DB solutions
 * Functional prototype (LLM + RAG + Vector DB)
 * Comprehensive documentation and knowledge transfer

## Description

* Deploy and manage open-source LLMs (e.g., Llama 3, Mistral/Mixtral) in on-prem or private environments
 * Develop and optimize LLM inference workflows using Python
 * Implement Retrieval-Augmented Generation (RAG) pipelines
 * Design and integrate vector database solutions for efficient semantic search
 * Perform model quantization and performance tuning for CPU-based inference
 * Ensure data privacy, security, and governance compliance in enterprise environments
 * Implement access controls, logging, and monitoring mechanisms
 * Deliver reference architecture, prototypes, and technical documentation
 * Collaborate with internal teams for knowledge transfer and system adoption


## Related Videos

- [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered)
- [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock)
- [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata)
- [Best practices: Building Enterprise Applications that leverage GenAI](https://www.wearedevelopers.com/videos/1513-best-practices-building-enterprise-applications-that-leverage-genai)
- [Building an AI-Ready Content Lake: Scaling RAG and Document AI Beyond Demos](https://www.wearedevelopers.com/videos/1977-building-an-ai-ready-content-lake-scaling-rag-and-document-ai-beyond-demos)
- [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker)

## Related Articles

- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)
- [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix)
- [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [Dev Digest 138 - Are you secure about this?](https://www.wearedevelopers.com/magazine/486-dev-digest-138-are-you-secure-about-this)