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Ai Rag Jobs in Michigan (NOW HIRING)

HTC Global Services Inc

AI Engineer

Grand Rapids, MI · On-site

Job Title AI/ML Solutions Architect (GenAI & RAG) Overview / Summary We are seeking an experienced AI/ML Solutions Architect with 10+ years of software engineering and/or data science experience ...

Harman International Industries

Senior Engineer, AI

Novi, MI · On-site

$98K - $134K/yr

Design and implement RAG pipelines across heterogeneous enterprise datasets, including requirements ... Implement responsible AI practices including guardrails, content filtering, access controls ...

Ford Motor Company

AI Software Engineer

Dearborn, MI · On-site

As an AI-focused Software Engineer in Marketing Enterprise Analytics, you will architect systems ... Implement advanced RAG pipelines (re-ranking, query transformation, and embedding optimization) to ...

Merican

AI Native Software Engineer

Detroit, MI · On-site

Retrieval (RAG) * Orchestration workflows * Tool/function invocation * Policy-based routing * Build ... Integrate with AI providers (e.g., OpenAI, Anthropic, Google Vertex, open-source models) * Build ...

Aquent

AI Software Developer

Ann Arbor, MI · On-site

$47.82 - $53.13/hr

Are you a passionate AI Engineer ready to transform the financial landscape with intelligent ... Implement retrieval-augmented generation (RAG), semantic search, and knowledge retrieval solutions ...

Judge Group, Inc.

Midlevel AI Developer

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.

Aquent Talent

AI Software Developer [211339]

Ann Arbor, MI · On-site

$47.82 - $53.13/hr

Are you a passionate AI Engineer ready to transform the financial landscape with intelligent ... Implement retrieval-augmented generation (RAG), semantic search, and knowledge retrieval solutions ...

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Ai Rag information

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.

Which AI is best at RAG?

For an AI Rag role, the best AI systems for Retrieval-Augmented Generation (RAG) tasks typically include models like OpenAI's GPT-4, Google's Bard, and Meta's Llama 2, which are capable of integrating retrieval components with language generation. Success in RAG depends on the model's ability to efficiently access and incorporate external data, as well as the implementation of effective retrieval mechanisms and fine-tuning. Skills in natural language processing, knowledge of retrieval systems, and experience with relevant tools are essential for this role.

What engineer makes 500,000 a year?

Senior software engineers, especially those working in high-demand fields like artificial intelligence or machine learning at large tech companies, can earn $500,000 or more annually. Compensation often includes base salary, bonuses, and stock options, and requires advanced skills, extensive experience, and often a master's or Ph.D. in a related field.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer, AI research director, or executive roles like AI CTO. These roles often require advanced skills in data science, deep learning, and experience with tools like TensorFlow or PyTorch, along with a strong track record of innovation and leadership in the field.

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.

Which 3 jobs will survive AI?

AI Rag is a role that involves managing and interpreting AI outputs, and jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to survive AI automation. Examples include healthcare professionals, skilled tradespeople, and roles in education. These jobs often require human judgment, interpersonal skills, and adaptability that AI cannot fully replicate.

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.
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What job categories do people searching Ai Rag jobs in Michigan look for? The top searched job categories for Ai Rag jobs in Michigan are:
What cities in Michigan are hiring for Ai Rag jobs? Cities in Michigan with the most Ai Rag job openings:
Ai Rag jobs near you
AI Agentic Engineer

AI Agentic Engineer

Tata Consultancy Services

Detroit, MI • On-site

Full-time

Posted 16 days ago

Tata Consultancy Services rating

6.5

Company rating: 6.5 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

159th of 210 rated it services

Job description

Job Summary:
Tata Consultancy Services is seeking an AI Agentic Engineer to architect and deploy advanced AI agents capable of autonomous reasoning and decision-making. The role involves developing robust RAG pipelines, maintaining tools for agent interactions, and ensuring the safety and reliability of AI systems in production environments.
Responsibilities:
• Architect, build, and deploy advanced AI agents capable of autonomous reasoning, decision-making, and self-directed task execution.
• Design and implement complex, multi-step agentic workflows that integrate with enterprise APIs, data sources, and platforms.
• Develop robust RAG pipelines to ground agent responses in factual, reliable data.
• This includes managing the full lifecycle from data ingestion and vectorization to retrieval and citation.
• Build and maintain the "tools" that agents use to interact with the digital world.
• Create secure, well-documented tool interfaces for internal services, databases, and third-party APIs.
• Design and implement comprehensive evaluation frameworks to measure agent performance, accuracy, and reliability.
• Develop and enforce safety guardrails, policy checks, and fallback mechanisms to ensure agents operate safely and predictably in production environments.
• Debug, monitor, and optimize agentic systems for latency, cost, and efficiency.
• Own the end-to-end deployment process, including CI/CD, structured logging, and incident response for AI systems.
Qualifications:
Required:
• Strong software engineering fundamentals with expert-level proficiency in Python.
• Experience with Java, Go, or TypeScript is a strong plus.
• Proven, hands-on experience building and deploying production-grade applications using Large Language Models (LLMs) like GPT, Claude, or Gemini.
• Experience with tool/function-calling, structured outputs, and evaluation.
• Demonstrable expertise in designing and implementing agentic workflows using frameworks like LangGraph, Semantic Kernel, AutoGen, or similar.
• Experience with multi-agent systems, planning, and autonomous execution.
• Deep, practical knowledge of building and optimizing RAG pipelines.
• Experience with data ingestion, various chunking strategies, embeddings, vector databases (e.g., Pinecone, Chroma, FAISS), and hybrid search/reranking.
• Experience with production engineering practices, including building scalable APIs (REST, RPC), microservices, CI/CD pipelines, containerization (Docker, Kubernetes), and cloud platforms (AWS, Azure, or GCP).
• Ability to analyze complex, ambiguous problems and design innovative, practical solutions.
• Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
• Proven experience working cross-functionally with product, research, and infrastructure teams.
• A bias for action and a strong sense of ownership.
• Capable of driving projects from conception to completion, mentoring junior engineers, and helping to define and influence AI strategy and best practices.
• BACHELOR OF COMPUTER SCIENCE
Company:
Tata Consultancy Services is a business solutions company that specializes on information technology services and consulting. It is a sub-organization of Tata Group. Founded in 1968, the company is headquartered in Mumbai, IND, with a team of 10001+ employees. The company is currently Late Stage.

What Tata Consultancy Services employees say

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About Tata Consultancy Services

Sourced by ZipRecruiter

Tata Consultancy Services is an IT services, consulting and business solutions organization that delivers real results to global business, ensuring a level of certainty no other firm can match. TCS offers a consulting-led, integrated portfolio of IT, BPO, infrastructure, engineering, and assurance services. This is delivered through its unique Global Network Delivery Model™, recognized as the benchmark of excellence in software development. TCS delivers a level of certainty that no other firm can match--to our clients and to our employees. Come join us and experience certainty in your career. TCS a global Consulting and IT Services firm that is ranked in the top quartile by industry analysts. Our 2021 fiscal revenues topped $25 B and our market capitalization is over $170+B, yet we have a deep and large history of philanthropy and corporate social responsibility. Now approaching 600K of the best IT professionals and consultants, we are a trusted advisor, guiding our clients' enterprises through growth and transformation journeys - helping them to become agile, intelligent, automated and on the cloud. We are devoted to DEI and are recognized as a top employer and place to work.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Edison, NJ, US

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