Ann Arbor, MI · On-site
$50 - $55/hr
Implement retrieval-augmented generation (RAG), semantic search, and knowledge retrieval solutions. Evaluate, benchmark, and optimize AI model performance, focusing on quality, cost, and latency.
Ann Arbor, MI · On-site
$50 - $55/hr
Implement retrieval-augmented generation (RAG), semantic search, and knowledge retrieval solutions. Evaluate, benchmark, and optimize AI model performance, focusing on quality, cost, and latency.
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
Dearborn, MI · On-site
$96K - $131K/yr
Strong understanding of Generative AI principles and architectures, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. * Proven experience in building and ...
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Dearborn, MI · On-site
$96K - $131K/yr
Strong understanding of Generative AI principles and architectures, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. * Proven experience in building and ...
$105K - $126K/yr
Strong understanding of Generative AI principles and architectures, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. * Proven experience in building and ...
Quick apply
$105K - $126K/yr
Strong understanding of Generative AI principles and architectures, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. * Proven experience in building and ...
Dearborn, MI · On-site
Develop and implement LLM-powered applications, including Retrieval-Augmented Generation (RAG), prompt orchestration, agentic workflows, and tool integrations. Create scalable APIs and AI services ...
Dearborn, MI · On-site
Develop and implement LLM-powered applications, including Retrieval-Augmented Generation (RAG), prompt orchestration, agentic workflows, and tool integrations. Create scalable APIs and AI services ...
Dearborn, MI · On-site
$105K - $126K/yr
Develop and implement LLM-powered applications, including Retrieval-Augmented Generation (RAG), prompt orchestration, agentic workflows, and tool integrations. Create scalable APIs and AI services ...
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Dearborn, MI · On-site
$105K - $126K/yr
Develop and implement LLM-powered applications, including Retrieval-Augmented Generation (RAG), prompt orchestration, agentic workflows, and tool integrations. Create scalable APIs and AI services ...
Ann Arbor, MI · On-site
$111K - $188K/yr
Implement retrieval-augmented generation (RAG) architectures using internal and external data sources * Design data pipelines and connectors to enterprise systems (e.g., databases, APIs, knowledge ...
Ann Arbor, MI · On-site
$111K - $188K/yr
Implement retrieval-augmented generation (RAG) architectures using internal and external data sources * Design data pipelines and connectors to enterprise systems (e.g., databases, APIs, knowledge ...
Detroit, MI · On-site
Architect and deliver integrated AI solutions, including agentic workflows, retrieval-augmented generation pipelines, and enterprise platform integrations * Define and enforce governance, security ...
Detroit, MI · On-site
Architect and deliver integrated AI solutions, including agentic workflows, retrieval-augmented generation pipelines, and enterprise platform integrations * Define and enforce governance, security ...
Auburn Hills, MI · On-site
$60.25 - $77.50/hr
We are seeking an experienced AI/ML Architect to design and develop conversational AI solutions using Retrieval-Augmented Generation (RAG) techniques. The ideal candidate will have a strong ...
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Auburn Hills, MI · On-site
$60.25 - $77.50/hr
We are seeking an experienced AI/ML Architect to design and develop conversational AI solutions using Retrieval-Augmented Generation (RAG) techniques. The ideal candidate will have a strong ...
Ann Arbor, MI · On-site
$111K - $188K/yr
Implement retrieval-augmented generation (RAG) architectures using internal and external data sources * Design data pipelines and connectors to enterprise systems (e.g., databases, APIs, knowledge ...
Ann Arbor, MI · On-site
$111K - $188K/yr
Implement retrieval-augmented generation (RAG) architectures using internal and external data sources * Design data pipelines and connectors to enterprise systems (e.g., databases, APIs, knowledge ...
Warren, MI · On-site
Leverage LLMs and related AI services (e.g., retrieval-augmented generation, embeddings, vector search) to power agent capabilities. * Integrate agents with enterprise systems, APIs, and data sources ...
Warren, MI · On-site
Leverage LLMs and related AI services (e.g., retrieval-augmented generation, embeddings, vector search) to power agent capabilities. * Integrate agents with enterprise systems, APIs, and data sources ...
Warren, MI · On-site +1
Leverage LLMs and related AI services (e.g., retrieval-augmented generation, embeddings, vector search) to power agent capabilities. * Integrate agents with enterprise systems, APIs, and data sources ...
Warren, MI · On-site +1
Leverage LLMs and related AI services (e.g., retrieval-augmented generation, embeddings, vector search) to power agent capabilities. * Integrate agents with enterprise systems, APIs, and data sources ...
Ann Arbor, MI · On-site
$111K - $188K/yr
Implement retrieval-augmented generation (RAG) architectures using internal and external data sources * Design data pipelines and connectors to enterprise systems (e.g., databases, APIs, knowledge ...
Ann Arbor, MI · On-site
$111K - $188K/yr
Implement retrieval-augmented generation (RAG) architectures using internal and external data sources * Design data pipelines and connectors to enterprise systems (e.g., databases, APIs, knowledge ...
Ann Arbor, MI · On-site
$111K - $188K/yr
Implement retrieval-augmented generation (RAG) architectures using internal and external data sources * Design data pipelines and connectors to enterprise systems (e.g., databases, APIs, knowledge ...
Ann Arbor, MI · On-site
$111K - $188K/yr
Implement retrieval-augmented generation (RAG) architectures using internal and external data sources * Design data pipelines and connectors to enterprise systems (e.g., databases, APIs, knowledge ...
... Retrieval Augmented Generation (RAG) solution. The ideal candidate should be capable of working across the full AI lifecycle, including ingestion, retrieval, modeling, APIs, testing, deployment ...
New
... Retrieval Augmented Generation (RAG) solution. The ideal candidate should be capable of working across the full AI lifecycle, including ingestion, retrieval, modeling, APIs, testing, deployment ...
New
... Retrieval Augmented Generation (RAG) solution. The ideal candidate should be capable of working across the full AI lifecycle, including ingestion, retrieval, modeling, APIs, testing, deployment ...
New
... Retrieval Augmented Generation (RAG) solution. The ideal candidate should be capable of working across the full AI lifecycle, including ingestion, retrieval, modeling, APIs, testing, deployment ...
New
Southfield, MI · Remote
$65 - $84.75/hr
The AI Architect will own and define reference architectures for Retrieval-Augmented Generation (RAG), Conversational AI, Document Intelligence, and Agentic AI, ensuring solutions are scalable ...
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Southfield, MI · Remote
$65 - $84.75/hr
The AI Architect will own and define reference architectures for Retrieval-Augmented Generation (RAG), Conversational AI, Document Intelligence, and Agentic AI, ensuring solutions are scalable ...
Warren, MI · On-site
... Retrieval-Augmented Generation) systems to enhance agent knowledge and context Create generative models for code generation, content creation, and strategic planning within agent frameworks Agent ...
Warren, MI · On-site
... Retrieval-Augmented Generation) systems to enhance agent knowledge and context Create generative models for code generation, content creation, and strategic planning within agent frameworks Agent ...
Experiment with and implement Retrieval Augmented Generation (RAG), embeddings, vector databases, and other AI-driven architectures * Create seamless full-stack experiences from database to user ...
Experiment with and implement Retrieval Augmented Generation (RAG), embeddings, vector databases, and other AI-driven architectures * Create seamless full-stack experiences from database to user ...
Exposure to LLM application patterns such as retrieval-augmented generation (RAG), prompt engineering, or evaluating AI output quality. * Hands-on usage of AI tools in your development workflow, such ...
Exposure to LLM application patterns such as retrieval-augmented generation (RAG), prompt engineering, or evaluating AI output quality. * Hands-on usage of AI tools in your development workflow, such ...
A Retrieval Augmented Generation engineer typically spends their day designing and implementing systems that combine information retrieval with advanced generative models, such as large language models. This includes fine-tuning models, integrating external data sources, developing vector search pipelines, and evaluating output quality. Collaboration with data scientists, machine learning engineers, and product teams is common to ensure the solutions meet user requirements and scale effectively. Additionally, RAG engineers often troubleshoot issues, monitor model performance in production, and stay informed about the latest advancements in AI and information retrieval.
A Retrieval Augmented Generation (RAG) job typically involves developing and optimizing AI systems that enhance text generation by incorporating external knowledge retrieved from relevant sources. Professionals in this field work on integrating retrieval mechanisms with large language models to improve the relevance, accuracy, and factual grounding of generated content. Common responsibilities include designing retrieval systems, fine-tuning language models, optimizing performance, and ensuring the seamless integration of factual data into AI-generated text. This role is highly interdisciplinary, involving expertise in natural language processing (NLP), machine learning, and information retrieval.
To thrive in a Retrieval Augmented Generation (RAG) engineering role, you need a solid background in machine learning, natural language processing (NLP), and experience with scalable information retrieval systems, typically supported by a relevant degree in computer science or a related field. Familiarity with tools such as Python, PyTorch or TensorFlow, vector databases, and search platforms like Elasticsearch is essential, along with practical experience deploying and tuning RAG pipelines. Strong problem-solving skills, a collaborative mindset, and effective communication abilities set outstanding professionals apart in this field. These competencies are crucial for designing, implementing, and optimizing hybrid retrieval-generation AI systems that address complex, real-world information needs.
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5,001 - 10,000 Employees
Wayne, PA, US
1970
