AI Engineer, LLM

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SAI Group

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 1997

📡 Telecommunications

⚡ Energy

🏗️ Construction

Telecommunications • Energy • Construction

SAI Group is a turnkey developer and contractor based in Salem, NH that provides wireless telecommunications, renewable energy, and construction services. The company offers full lifecycle site development for wireless networks — including RF engineering, DAS services, tower antenna/cable crews, electricians, installation, commissioning and optimization — and emphasizes in-house capabilities, quality control and schedule/cost management. SAI also develops renewable energy projects and infrastructure such as electric vehicle charging, solar power and energy storage solutions, and performs residential and commercial construction work. Founded in 1998, SAI highlights the ability to self-perform over 90% of development tasks and serves clients seeking integrated telecom and energy development services.

📋 Description

• Design, develop, and deploy LLM-powered applications and AI agents. • Build Retrieval-Augmented Generation (RAG) pipelines using vector databases. • Develop prompt engineering strategies and optimize model performance. • Integrate LLM APIs (OpenAI, Anthropic, Google Gemini, Azure OpenAI, etc.) into applications. • Fine-tune and evaluate open-source LLMs where applicable. • Develop AI workflows using frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or similar. • Build REST APIs and microservices for AI applications. • Implement AI guardrails, content moderation, and security best practices. • Optimize inference performance, latency, and operational costs. • Collaborate with cross-functional teams to deliver production-ready AI solutions. • Stay current with emerging AI technologies, research, and industry trends.

🎯 Requirements

• Strong proficiency in Python. • Experience with Large Language Models and Generative AI. • Hands-on experience with LangChain, LlamaIndex, CrewAI, AutoGen, or similar frameworks. • Knowledge of RAG architectures and vector databases (Pinecone, Weaviate, Chroma, FAISS, Milvus, etc.). • Experience with embedding models and semantic search. • Familiarity with OpenAI, Anthropic, Gemini, Azure OpenAI, or open-source LLMs (Llama, Mistral, Qwen, etc.). • Experience with FastAPI, Flask, or Django. • Strong understanding of REST APIs and cloud platforms (AWS, Azure, or GCP). • Knowledge of Docker, Kubernetes, and CI/CD pipelines. • Familiarity with Git and software development best practices. • Understanding of AI evaluation metrics, prompt optimization, and model monitoring.