Lead GenAI Engineer - GCP & Enterprise AI Systems

Robotics Technologies LLC; Minneapolis (MN); On-site; USD 77,000 - 110,000; Full time

Job summary

Robotics Technologies LLC in Minneapolis, MN, seeks a Lead Software Engineer to architect and build GenAI/GCP solutions for enterprise use. You will design, implement, and scale AI systems with a focus on reliability and production readiness.

Responsibilities include building RAG apps, fine-tuning LLMs, document processing with DocAI, and integrating with Vertex AI, LangGraph, and containerized deployments in cloud environments (GCP/AWS/Azure).

Qualifications

• Strong hands-on experience with Python, Google Vertex AI, and Google Document AI (DocAI).
• Experience building enterprise-grade Generative AI and LLM solutions.
• Experience with LLM fine-tuning, deployment, and performance tuning.
• Develop intelligent document processing with OCR and DocAI.
• Strong cloud experience with GCP, AWS, or Azure.

Responsibilities

• 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.
• Develop scalable AI applications using Python, FastAPI, Flask, and REST APIs.
• Experience with Docker and containerized application deployment.
• Hands-on experience with vector databases, embedding models, and semantic search.
• Build and integrate AI-powered applications for enterprise business use cases.
• Optimize AI solutions for scalability, reliability, performance, and production deployment.

Skills

Python

Vertex AI

DocAI

LLMs

Fine-tuning

NLP

PyTorch

Vector DB

Embeddings

Semantic search

FastAPI

Flask

REST APIs

Docker

Tools

Docker

Job description

Robotics Technologies LLC in Minneapolis, MN, seeks a Lead Software Engineer to architect and build GenAI/GCP solutions for enterprise use. You will design, implement, and scale AI systems with a focus on reliability and production readiness.

Responsibilities include building RAG apps, fine-tuning LLMs, document processing with DocAI, and integrating with Vertex AI, LangGraph, and containerized deployments in cloud environments (GCP/AWS/Azure).