> Markdown version of [/jobs/ext/4014064-senior-data-engineer-agentic-ai-rag-platform](https://www.wearedevelopers.com/jobs/ext/4014064-senior-data-engineer-agentic-ai-rag-platform). 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). --- # Senior Data Engineer (Agentic AI / RAG Platform) - **Company:** TechDigital Corporation - **Location:** Dearborn, MI, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Microsoft Azure, Data as a Services, Information Engineering, Data Stores, Data Systems, Information Retrieval, Python (Programming Language), Metadata, OpenAI, Cloud Services, Search Technologies, SQL Databases, Technical Data Management Systems, Retrieval-Augmented Generation, Prompt Engineering, Apache Spark, Generative AI, Agentic-AI, Integration Frameworks, Model Context Protocol, Data Pipelines - **Published:** October 29, 2026 - **Apply:** https://www.thejobnetwork.com/job/081cb722-ab3f-41a9-8d42-74a7fdccde9d/senior-data-engineer-agentic-ai-rag-platform ## About the Role * 10 years of experience in Data Engineering. * Strong expertise in Python, Spark, SQL, and data processing frameworks. * Experience building cloud-native data pipelines. * Deep understanding of vector databases and embeddings. * Experience with Retrieval-Augmented Generation (RAG). * Knowledge of Agentic AI architectures. * Experience designing metadata-driven data solutions. Preferred Skills * Experience with Azure OpenAI, Vertex AI, LangChain, or similar frameworks. * Knowledge of MCP (Model Context Protocol). * Automotive, engineering, or manufacturing data experience Top Skills: Data Engineering Python, Spark, SQL, and data processing frameworks Agentic AI, RAG ## Description * Integrate structured and unstructured data sources into VESSEL. * Design and implement data ingestion pipelines. * Create vectorized data repositories for AI applications. * Develop semantic search and knowledge retrieval frameworks. * Build data services supporting AI agents and prompt engineering. * Design scalable cloud-native data platforms. * Optimize data quality, governance, and performance.