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Ai Rag Jobs in Rochester Hills, MI (NOW HIRING)

Do you enjoy designing the systems behind AI agents, RAG applications, and data pipelines that run in real environments with data, security, and reliability constraints? If you're energized by ...

Agentic SQL retrieval, MCP integration, agentic tool use, as well as vector databases & RAG ... AI Evaluation & Production Readiness : defining evaluation methods, testing model behavior ...

Do you enjoy designing the systems behind AI agents, RAG applications, and data pipelines that run in real environments with data, security, and reliability constraints? If you're energized by ...

Implement RAG and document intelligence patterns (ingestion, chunking, embeddings, vector/hybrid ... AI Engineer Consultant Our Deloitte Human Capital team transforms technology platforms, drives ...

Do you enjoy designing the systems behind AI agents, RAG applications, and data pipelines that run in real environments with data, security, and reliability constraints? If you're energized by ...

You will architect, develop, and maintain production-grade systems encompassing RAG pipelines ... and AI systems that support GenAI use cases including RAG, agentic workflows, and model ...

We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ... Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector ...

Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector ... AI Engineer III Position Summary Our Deloitte Human Capital team transforms technology platforms ...

Google AI Lead Architect

Detroit, MI

$54.75 - $75/hr

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

You are a hybrid architect developer who excels at translating complex AI concepts-such as Agentic workflows, orchestration patterns, and RAG architectures-into "Golden Path" reference ...

AI Engineer (W2 Position) Location : Dearborn, MI (Hybrid) Duration: 12+ Months Experience: 8+ ... Experience with RAG, Lang Graph, NLP to SQL, ADK, and A2A Behavioral and Technical Interviews ...

AI Engineer Senior Consultant

Detroit, MI · Hybrid

$103K - $142K/yr

Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector ... AI Engineer Senior Consultant Our Deloitte Human Capital team transforms technology platforms ...

Build AI-powered applications that support engineering, operations, manufacturing, and business ... Familiarity with Retrieval-Augmented Generation (RAG), Vector databases, Cloud platforms, Docker ...

... RAG pipelines, and working with vector indexing (e.g., Pinecone, Weaviate, Azure AI Search) • ... Deep proficiency in Azure and/or AWS AI services, serverless inference, and managed Kubernetes ...

You are a hybrid architect developer who excels at translating complex AI concepts-such as Agentic workflows, orchestration patterns, and RAG architectures-into "Golden Path" reference ...

Integrate LLMs, RAG systems, and agentic workflows into HED platform architectures Platform Integration & Engineering * Integrate AI features into existing HED platform architectures and data systems

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Ai Rag information

See Rochester Hills, MI salary details

$29.5K

$53.6K

$76.9K

How much do ai rag jobs pay per year?

As of Jun 16, 2026, the average yearly pay for ai rag in Rochester Hills, MI is $53,612.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,100.00 and $59,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI Researcher, and why are they important?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What are AI RAGs?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What are some common challenges faced by AI RAG (Retrieval-Augmented Generation) engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.
What cities near Rochester Hills, MI are hiring for Ai Rag jobs? Cities near Rochester Hills, MI with the most Ai Rag job openings:
Infographic showing various Ai Rag job openings in Rochester Hills, MI as of June 2026, with employment types broken down into 100% Full Time. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $53,612 per year, or $25.8 per hour.
AI Architect (with Azure)-Remote : Contract on w2

AI Architect (with Azure)-Remote : Contract on w2

Marvel Technologies Inc

Southfield, MI • Remote

$65 - $84.75/hr

Contractor

Posted 21 days ago


Job description

Job Title :  AI Architect (with Azure)

Location :   Remote-USA

Duration : Long Term Contract

Contract on w2

Domain- Preferred Insurance.

Experience: 15+ years

Role Overview:

We are seeking a highly skilled AI Azure Architect to lead the architecture and technical strategy for AI programs across insurance and other regulated industries. 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, secure, compliant, and deliver measurable business value on AWS cloud/Azure Cloud.

Key Responsibilities:

  • Define end-to-end AI architectures covering ingestion → storage → retrieval → reasoning → action → monitoring.
  • Own and evolve reference architectures for Document AI, Conversational AI, and Agentic AI.
  • Specify non-functional requirements (latency, throughput, privacy, compliance, observability, cost).
  • Select and justify AWS-native AI/ML services (Bedrock, SageMaker, Kendra, OpenSearch, etc.) and third-party tools.

OR

  • Select and justify Azure-native AI/ML Services - Azure AI Foundry, Azure SDK, Cosmos DB, Azure OpenAI, Azure Blob Storage, Azure AI Search, Azure Cognitive Services, Service Principals, and Azure Agent (critical for agentic workflows).
  • Govern prompt/version management, enforce safety policies, and manage controls for prompt injection and PII protection.
  • Lead PoCs to production with AWS-based templates and golden paths.
  • Collaborate with stakeholders; mentor engineers; conduct design/code reviews.
  • Establish measurement frameworks (hallucination rate, groundedness, answer quality, CSAT, deflection).
  • Ensure seamless AWS/Azure enterprise integrations with insurance platforms (policy, claims, underwriting).

Required Skills & Experience:

  • 15+ years in AI/ML software, 3–5+ years in solution/enterprise architecture.
  • Proven experience designing AI systems at enterprise scale on AWS/Azure.
  • Hands-on with AWS Bedrock, SageMaker, Lambda, Kendra, OpenSearch, Redshift, DynamoDB, S3.

OR

  • Hands on Azure AI Foundry, Azure SDK, Cosmos DB, Azure OpenAI, Service Principals, Azure Blob, Azure AI Search, Azure Cognitive Services, and Azure Agent.
  • Expertise in LLMs, vector databases, RAG pipelines, and agentic workflows.
  • Strong multi-cloud cost/latency tradeoff knowledge.
  • Excellent communication, stakeholder engagement, and blueprinting skills.
  • Insurance industry experience strongly preferred (FNOL, claims adjudication, underwriting, billing, policy servicing).