Sr. GenAI Engineer (LLM/RAG) - (Only on W2)
Role overview
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.
Primary Skiils Required:
GenAI/RAG, LLMs, Python, FastAPI, vector search, ElasticSearch, Airflow/Astronomer, Tekton CI/CD, cloud & distributed systems.
Responsibilities
- check_circle GenAI Application Development**
- check_circle Design and build scalable GenAI-powered applications using Python and FastAPI.
- check_circle Develop and deploy Retrieval-Augmented Generation pipelines using vector search and hybrid retrieval strategies
- check_circle Integrate large language models with enterprise data sources.
- check_circle Implement evaluation frameworks to measure RAG accuracy, retrieval quality, and response relevance.
- check_circle Develop high-performance APIs using FastAPI.
- check_circle Implement data pipelines and orchestration workflows using Airflow and Astronomer.
- check_circle Build CI/CD workflows using Tekton.
- check_circle Design scalable search systems using ElasticSearch and vector databases
- check_circle Design vector search architectures for structured and unstructured data.
- check_circle Implement embedding pipelines and similarity search strategies.
- check_circle Optimize search relevance, latency, and system performance.
- check_circle Evaluate and continuously improve RAG effectiveness.
- check_circle Build ingestion, transformation, and inference pipelines.
- check_circle Manage DAG-based workflows using Airflow.
- check_circle Ensure reliability, scalability, and observability of AI systems.
- check_circle Translate Automotive Sales, Services, and Warranty business requirements into AI-driven solutions.
- check_circle Work closely with business stakeholders to optimize parts pricing and warranty claims workflows using AI.
- check_circle 9+ years of experience in software engineering and AI-driven application development.
- check_circle Strong proficiency in Python.
- check_circle Experience with FastAPI for backend services.
- check_circle Hands-on experience with RAG techniques and vector search implementations.
- check_circle Experience evaluating and tuning RAG systems.
- check_circle Expertise in ElasticSearch.
- check_circle Experience with Airflow and Astronomer for workflow orchestration.
- check_circle Experience implementing CI/CD pipelines using Tekton.
- check_circle Solid understanding of embedding models, similarity search, and retrieval optimization
- check_circle 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.
- Bachelor’s Degree in Computer Science, Engineering, or related field required.
Tags & Focus Areas
About Miracle Software Systems, Inc
We Miracle Software Systems is looking for the AI Engineer on W2/Fulltime