> Markdown version of [/jobs/ext/2028983-genai-engineer](https://www.wearedevelopers.com/jobs/ext/2028983-genai-engineer). 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). --- # GenAI Engineer - **Company:** Corporate Brokers, LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Computing, Information Engineering, Data Transformation, Data Mining, Python (Programming Language), Machine Learning, Natural Language Processing, Open Source Technology, Tensorflow, SQL Databases, Unstructured Data, Cloud Platform System, Generative AI, Containerization, Scikit Learn, Kubernetes, Information Technology, HuggingFace, Xgboost, Machine Learning Operations, Virtual Agents, Docker - **Published:** August 11, 2026 - **Apply:** https://public-rest40.bullhornstaffing.com/rest-services/BJ529/query/JobBoardPost?where=id=19387&fields=id,title,publishedCategory(id,name),address(city,state),employmentType,dateLastPublished,publicDescription,isOpen,isPublic,isDeleted ## About the Role * Generative AI & Agentic Frameworks: Hands-on experience developing RAG pipelines and building Agentic flows using open-source and closed-source models. Clear conceptual understanding of Agentic flows versus basic automation. * Core Technical Stack: Advanced proficiency in Python and SQL for data analysis, data transformation, model development, and pipeline execution. * Data Engineering & Workflow: Strong data transformation experience working with varied data sources across cloud providers. * Data Types: Practical experience handling both structured and unstructured data, including NLP methods for data extraction. * Machine Learning: Solid foundation in machine learning concepts and hands-on experience with standard ML frameworks (e.g., scikit-learn, XGBoost, LightGBM, Hugging Face). * Cloud & Infrastructure: Familiarity with cloud platforms (AWS, Azure, or GCP), MLOps practices, and containerization tools (Docker/Kubernetes). * Education & Experience: Bachelor's degree required; 4+ years of hands-on data science or machine learning experience., * Bachelor's degree in a quantitative field (Computer Science, Data Science, Statistics, Mathematics, or related field). #LI-SB1 #LI-Remote ## Description We are seeking three Senior GenAI / Machine Learning Engineers to join a high-impact technical team working on enterprise Generative AI projects. This role requires strong foundations in machine learning and data engineering, paired with hands-on expertise in building RAG pipelines and Agentic AI frameworks. You will work across diverse datasets, cloud environments, and data workflows to construct production-ready AI solution flows., * Design, build, and deploy Generative AI applications, specifically focused on RAG pipelines and Agentic AI workflows. * Develop complex data workflows and transformation pipelines handling both structured and unstructured data. * Utilize NLP techniques to extract valuable insights from unstructured data sources across multiple cloud platforms. * Implement end-to-end machine learning models and frameworks using Python and SQL. * Distinguish between standard process automation and true Agentic flows to architect optimal system solutions. * Work with disparate data sources across cloud environments (AWS, Azure, or GCP). ## Related Videos - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [The State of GenAI & Machine Learning in 2025](https://www.wearedevelopers.com/videos/1383-the-state-of-genai-machine-learning-in-2025) - [Microservices: how to get started with Spring Boot and Kubernetes](https://www.wearedevelopers.com/videos/242-microservices-how-to-get-started-with-spring-boot-and-kubernetes) - [Instant KAI Sandboxes with vCluster: Multi-Tenant, Multi-Scheduler GPU Sharing](https://www.wearedevelopers.com/videos/100333-instant-kai-sandboxes-with-vcluster-multi-tenant-multi-scheduler-gpu-sharing) ## Related Articles - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)