Our engineers design and build production-grade RAG pipelines with advanced chunking strategies, hybrid search, re-ranking, and evaluation frameworks that deliver accurate, hallucination-free responses from your proprietary data.
Fine-tune open-source and commercial LLMs for your specific domain with our engineers experienced in LoRA, QLoRA, RLHF, and distillation techniques to improve accuracy while reducing inference costs.
Hire individual RAG/LLM engineers or build a dedicated AI team. Our engineers work in your timezone and integrate seamlessly with your existing development processes and data infrastructure.
Discover why companies hire RAG and LLM engineers through Pine Technologies.
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What skills do your RAG/LLM engineers have?
Our RAG/LLM engineers are proficient in Python, LangChain, LlamaIndex, vector databases (Pinecone, Weaviate, Qdrant, ChromaDB), embedding models, prompt engineering, LLM fine-tuning (LoRA, QLoRA), evaluation frameworks (RAGAS, DeepEval), and cloud AI platforms. They have deep experience in chunking strategies, hybrid search, re-ranking, and production deployment of RAG systems.
How quickly can I hire a RAG/LLM engineer?
We can match you with a pre-vetted RAG/LLM engineer within 48-72 hours and have them onboarded and working within 1-2 weeks. For specialized requirements like fine-tuning expertise or specific vector database experience, the matching process may take slightly longer.
What types of RAG systems can your engineers build?
Our engineers build document Q&A systems, knowledge base chatbots, semantic search engines, multi-modal RAG pipelines, agentic RAG systems, and enterprise-grade retrieval platforms. They handle complex scenarios including multi-tenant RAG, conversational retrieval with memory, and hybrid search combining dense and sparse retrieval.
Can your engineers fine-tune LLMs for our specific use case?
Yes, our engineers have extensive experience fine-tuning both open-source models (Llama, Mistral, Phi) and commercial models using techniques like LoRA, QLoRA, and RLHF. They handle dataset preparation, training pipeline setup, evaluation, and deployment of fine-tuned models optimized for your domain and cost requirements.
How do you vet your RAG/LLM engineers?
Our vetting process includes technical assessments covering RAG architecture design, hands-on challenges building retrieval pipelines with real datasets, evaluation of embedding and chunking strategy decisions, LLM prompt engineering proficiency, portfolio review of past RAG/LLM projects, and communication and collaboration assessments.
What is the cost of hiring a RAG/LLM engineer?
Our RAG/LLM engineers are available starting at $1500/month for full-time engagement. Rates vary based on seniority, specialization, and engagement duration. We offer flexible contracts with no long-term lock-in, allowing you to scale up or down as needed.
Pine Technologies is a custom software development company and IT staff augmentation agency headquartered in Pakistan and registered as a legal entity in Texas, USA. We help businesses in the United States, United Kingdom, European Union, and Australia hire pre-vetted RAG & LLM Engineers and other technology professionals. Our flexible engagement models start at $1,500/month with no long-term lock-in, timezone-flexible teams, and rigorous technical vetting to ensure you get top-tier talent.
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