Ai Rag Jobs in Mount Prospect, IL (NOW HIRING)

RAG and LLM application architecture; multi-agent workflows; MCP/tool calling; LangGraph/Semantic Kernel/OpenAI Agents SDK or similar; CI/CD; AIOps/MLOps; LLM/RAG/agent evaluation; AI observability ...

The ideal candidate will bring deep expertise in Python, FastAPI, and Retrieval-Augmented Generation (RAG) solutions, with hands-on experience deploying scalable AI applications on Azure. This role ...

Experience designing AI-enabled applications leveraging LLMs, RAG, or agent-based solutions. * Strong communication, consulting, and stakeholder management skills. Preferred Qualifications

RAG; autonomous decision frameworks; Python/R/SQL/SAS; vector databases; semantic search; knowledge graphs; metadata management; production ML/AI deployment, monitoring, governance, explainability ...

RAG and LLM application architecture; multi-agent workflows; MCP/tool calling; LangGraph/Semantic Kernel/OpenAI Agents SDK or similar; CI/CD; AIOps/MLOps; LLM/RAG/agent evaluation; AI observability ...

... RAG, embeddings, prompt engineering, and agents • Solid understanding of data engineering concepts, SQL/NoSQL, and feature pipelines • Experience deploying AI solutions on cloud platforms (GCP ...

Must Have Technical/Functional Skills • Python engineering • Production AI/ML coding • Databricks • MLflow • Azure AI Foundry • RAG architecture • LLM application architecture • ...

The ideal candidate will have hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, vector databases, and cloud-native AI ...

RAG and Agentic AI systems; Python; model serving frameworks and API development such as FastAPI/MLflow; vector databases and embeddings; LangChain/LlamaIndex or similar orchestration; CI/CD ...

GCP Gemini AI Developer (3-5 Years Experience) Location: Remote / Hybrid - Chicago preferred ... Reusable components adopted in at least 3 future use cases. 3. RAG / Context-Aware Workflows ...

From early-stage use case discovery through production deployment and monitoring, you'll work across the full AI lifecycle-leveraging large language models (LLMs), retrieval-augmented generation (RAG ...

... AI, RAG Pipelines, Python, Amplitude, and Jellyfish to drive enterprise AI tooling strategy, governance, implementation, platform adoption, and engineering productivity across a regulated environment.

This position combines deep hands-on expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI architectures with strong technical leadership to deliver secure ...

Implement agent architectures including tool use, multi-step workflows, and retrieval-augmented generation (RAG) patterns * Integrate AI agents with enterprise systems, APIs, and data sources

Proposing and implementing innovative solutions to complex problems • Experienced with Generative AI, RAG and GraphRAG patterns • Design models to predict next-best-action, customer behavior, and ...

Design and build AI solutions that accelerate data migration from legacy systems to the cloud ... Strong coding fluency in Python; hands-on experience with BigQuery, Claude Code, RAG architectures ...

... RAG pipelines leveraging vector search, embeddings, semantic ranking, and enterprise data sources (structured unstructured). • Develop prompt strategies, memory frameworks, and metadata tagging to ...

Leverage cutting-edge AI innovation - Experiment with cutting-edge LLMs and foundation models, architect RAG implementations, design sophisticated agentic systems, and develop Model Context Protocol ...

Leverage cutting-edge AI innovation - Experiment with cutting-edge LLMs and foundation models, architect RAG implementations, design sophisticated agentic systems, and develop Model Context Protocol ...

Develop RAG pipelines, embedding strategies, and vector search architectures. * Build agentic workflows, prompt strategies, and orchestration patterns. * Own AI/ML solutions end to end from design ...