> Markdown version of [/jobs/ext/3651081-ai-ml-engineer-internal-platforms](https://www.wearedevelopers.com/jobs/ext/3651081-ai-ml-engineer-internal-platforms). 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). --- # AI/ML Engineer, Internal Platforms - **Company:** ROOSEVELT PARENT-TEACHER ORGANIZATION OF RIVER FOREST, ILLINOIS - **Location:** United States (Remote available) - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Python (Programming Language), Machine Learning, Google Cloud, Cloud Platform System, LangChain, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Model Validation, Software Application Programming, Llamaindex, Backend, Agentic-AI, Fastapi, Virtual Agents, Api Design - **Published:** October 9, 2026 - **Apply:** https://www.juju.com/job/18_5339_487780 ## About the Role * Strong Python software engineering skills. * Experience building applications with LLMs and AI APIs. * Familiarity with LangChain, LangGraph, LlamaIndex, or similar agent frameworks. * Experience building APIs with FastAPI or comparable frameworks. * Experience with AWS, GCP, Azure, or another cloud platform. * Strong problem solving skills, an experimental mindset, and excellent communication and collaboration skills., * Experience shipping AI products or AI agents to production. * Familiarity with retrieval augmented generation, tool calling, model evaluation, or prompt engineering. * Contributions to open source AI projects or personal AI applications. * Experience in fast paced, AI first environments. ## Description * Build and improve AI agent capabilities using modern large language models. * Develop backend services and APIs in Python. * Design and refine prompts, workflows, retrieval augmented generation, and agent orchestration. * Evaluate model performance and improve quality through ongoing experimentation. * Partner with product and engineering teams to deliver AI powered features. * Deploy and maintain scalable AI systems in production. * Stay current with emerging AI models, tools, and engineering practices.