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# Lead Software Engineer - GenAI / GCP

- **Company:** Robotics Technologies LLC
- **Location:** Minneapolis, MN, United States
- **Experience:** Expert
- **Salary:** $141,440
- **Contract:** Temporary contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Cloud Computing, Data Mining, Google Docs, Python (Programming Language), Machine Learning, Natural Language Processing, Open Source Technology, Performance Tuning, OpenAI, Search Technologies, Software Deployment, Pytorch, Retrieval-Augmented Generation, Transfer Learning, Flask (Web Framework), Large Language Models, Google Vertex AI, Deep Learning, Generative AI, Agentic-AI, Fastapi, Containerization, CrewAI, Restful APIs, Intelligent Document Processing, Docker
- **Published:** November 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=78fbc755fae3779e

## About the Role

* Strong hands-on experience in Python, Google Vertex AI, and Google Document AI (DocAI).
 * Design, develop, and implement enterprise-grade Generative AI and LLM-based solutions.
 * Build RAG-based applications using retrieval, embeddings, and vector databases.
 * Implement enterprise-level Agentic AI workflows using LangGraph, Google ADK, CrewAI, or similar frameworks.
 * Experience with LLM fine-tuning, deployment, optimization, and performance tuning.
 * Develop intelligent document processing solutions using OCR, Google Document AI, and automated data extraction.
 * Strong understanding of NLP, Machine Learning, Deep Learning, and PyTorch.
 * Experience working with OpenAI APIs and open-source Large Language Models (LLMs).
 * Hands-on experience with vector databases, embedding models, and semantic search.
 * Develop scalable AI applications using Python, FastAPI, Flask, and REST APIs.
 * Experience with Docker and containerized application deployment.
 * Strong cloud experience with GCP, AWS, or Azure.
 * Build and integrate AI-powered applications for enterprise business use cases.
 * Optimize AI solutions for scalability, reliability, performance, and production deployment