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# Generative AI Engineer

- **Company:** Miracle Software Systems, Inc.
- **Location:** Dearborn, MI, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automated Storage and Retrieval Systems, Cloud Computing, Continuous Integration, Python (Programming Language), Machine Learning, Standard Sql, Software Deployment, Software Engineering, Data Processing, Google Cloud, Enterprise Software Applications, Large Language Models, Prompt Engineering, Generative AI, Git, Fastapi, AI Platforms, Machine Learning Operations, Virtual Agents, Restful APIs, Data Pipelines, Docker
- **Published:** June 18, 2026
- **Apply:** https://www.dice.com/job-detail/1d3699af-561f-468f-9f12-949218331be4

## About the Role

5+ years of software engineering experience.

Strong proficiency in Python.

Experience working with LLMs and Generative AI applications.

Experience building RAG systems and working with vector databases.

Experience developing REST APIs (FastAPI or similar frameworks).

Strong knowledge of SQL and data processing.

Experience with cloud platforms such as Google Cloud Platform.

Experience with Git and Docker.

Preferred Qualifications

Experience deploying AI/ML solutions in production environments.

Experience integrating LLM APIs (OpenAI or similar platforms).

Familiarity with LangChain, LlamaIndex, or similar frameworks.

Experience with vector databases (Pinecone, Weaviate, FAISS, etc.).

Understanding of MLOps and CI/CD pipelines.

## Description

Description: We are seeking a Generative AI Engineer to design, develop, and deploy AI-driven applications using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) architectures. In this role, you will build scalable AI solutions that integrate enterprise data with modern cloud platforms, APIs, and vector databases to enable intelligent automation and advanced analytics.

Responsibilities

Design and develop Generative AI applications using LLMs.

Build and optimize RAG pipelines using vector databases and embeddings.

Develop scalable APIs for AI services using frameworks such as FastAPI.

Implement prompt engineering and model optimization techniques.

Build and manage data pipelines for AI training and retrieval systems.

Deploy and maintain AI solutions on Google Cloud Platform (Google Cloud Platform).

Apply containerization (Docker) and CI/CD practices for production deployment.

Collaborate with cross-functional teams to integrate AI capabilities into enterprise applications.


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