GenAI Engineer

Miracle Software Systems

  • Dearborn, MI
  • 1 day ago
  • Contractor
  • Full-time

Highlights

The role focuses on designing and developing Retrieval-Augmented Generation (RAG) systems, vector search architectures, and scalable GenAI-powered platforms using modern Python-based backend frameworks. The ideal candidate combines strong backend engineering expertise with hands-on experience in advanced retrieval systems and real-world business use cases.

Numbers & Facts

LocationDearborn, MI
Job TypeContractor, Full-time

Description

Title: AI Engineer

Location: Dearborn, MI

Duration: Long-term

 

Position Summary

We are seeking a Senior GenAI Engineer with 9+ years of experience in building production-grade AI and data-driven applications. The role focuses on designing and developing Retrieval-Augmented Generation (RAG) systems, vector search architectures, and scalable GenAI-powered platforms using modern Python-based backend frameworks.

The ideal candidate combines strong backend engineering expertise with hands-on experience in advanced retrieval systems and real-world business use cases. Automotive domain knowledge in Sales, Services, Parts Pricing, and Warranty Claims is highly preferred.

Job Responsibilities

Skills : Python, FastAPI, GenAI/RAG, LLMs, vector search, ElasticSearch, Airflow/Astronomer, Tekton CI/CD, cloud & distributed systems.

 

Key Responsibilities

 

1. GenAI Application Development

Design and build scalable GenAI-powered applications using Python and FastAPI.

Develop and deploy Retrieval-Augmented Generation pipelines using vector search and hybrid retrieval strategies.

Integrate large language models with enterprise data sources.

Implement evaluation frameworks to measure RAG accuracy, retrieval quality, and response relevance.

 

2. Backend & Platform Engineering

Develop high-performance APIs using FastAPI.

Implement data pipelines and orchestration workflows using Airflow and Astronomer.

Build CI/CD workflows using Tekton.

Design scalable search systems using ElasticSearch and vector databases.

 

3. Retrieval & Search Architecture

Design vector search architectures for structured and unstructured data.

Implement embedding pipelines and similarity search strategies.

Optimize search relevance, latency, and system performance.

Evaluate and continuously improve RAG effectiveness.

 

4. Data & Workflow Orchestration

Build ingestion, transformation, and inference pipelines.

Manage DAG-based workflows using Airflow.

Ensure reliability, scalability, and observability of AI systems.

 

5. Domain Collaboration

Translate Automotive Sales, Services, and Warranty business requirements into AI-driven solutions.

Work closely with business stakeholders to optimize parts pricing and warranty claims workflows using AI.

 

Required Skills & Experience

9+ years of experience in software engineering and AI-driven application development.

Strong proficiency in Python.

Experience with FastAPI for backend services.

Hands-on experience with RAG techniques and vector search implementations.

Experience evaluating and tuning RAG systems.

Expertise in ElasticSearch.

Experience with Airflow and Astronomer for workflow orchestration.

Experience implementing CI/CD pipelines using Tekton.

Solid understanding of embedding models, similarity search, and retrieval optimization.

Experience building production-grade APIs and distributed systems.

 

Preferred Qualifications

Experience in Automotive Sales and Services.

Exposure to Parts Pricing and Warranty Claims processes.

Experience deploying GenAI applications in cloud environments.

Familiarity with evaluation frameworks for LLM-based systems.

 

Education

Bachelor’s Degree in Computer Science, Engineering, or related field required.

Master’s Degree preferred.

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