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Ai Rag Jobs in Minnesota (NOW HIRING)

Augeo Affinity Marketing

AI Architect

Saint Paul, MN · On-site

With the power of AI, we're unlocking capabilities that were never before possible - unifying ... LLM integration, prompt engineering, tool calling, RAG, evaluation, and orchestration * Strong ...

Genesys

Experience building RAG-based systems, vector databases, and semantic search architectures. * Demonstrated ability to lead large-scale AI initiatives and influence technical strategy. * Deep ...

3M

Architect - Agentic AI

Maplewood, MN · On-site

$188K - $230K/yr

Experience with RAG/memory architecture (chunking, embeddings, vector DBs, enterprise search ... Service/AI foundry) and routing across multiple model providers. * Familiarity with agent ...

3M

Architect - Agentic AI

Maplewood, MN · On-site

$188K - $230K/yr

Experience with RAG/memory architecture (chunking, embeddings, vector DBs, enterprise search ... Service/AI foundry) and routing across multiple model providers. * Familiarity with agent ...

UnitedHealth Group

Senior AI/ML Engineer

Eden Prairie, MN · On-site

$106K - $146K/yr

Design and implement retrieval-augmented generation (RAG) pipelines including document ingestion, chunking strategies, embedding generation, and vector database integration * Build agentic AI systems ...

UnitedHealth Group

Senior AI/ML Engineer

Eden Prairie, MN · On-site +1

$106K - $146K/yr

Design and implement retrievalaugmented generation (RAG) pipelines including document ingestion, chunking strategies, embedding generation, and vector database integration * Build agentic AI systems ...

US Bank

Gen AI Engineering Senior Director

Hopkins, MN · On-site

Lead the vision, architecture, and roadmap for enterprise AI platforms, including GenAI, LLM integration, Retrieval-Augmented Generation (RAG), and AI-driven search. * Provide technical leadership ...

US Bank

Senior AI Platform Engineer

Hopkins, MN

$56 - $72.25/hr

Retrieval-Augmented Generation (RAG) architectures * Prompt engineering techniques * Agentic AI concepts and workflows * Build intelligent pipelines using frameworks such as LangChain, LangGraph, and ...

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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.
What are popular job titles related to Ai Rag jobs in Minnesota? For Ai Rag jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Ai Rag jobs in Minnesota look for? The top searched job categories for Ai Rag jobs in Minnesota are:
What cities in Minnesota are hiring for Ai Rag jobs? Cities in Minnesota with the most Ai Rag job openings:
Ai Rag jobs near you

Senior AI Project Manager

Tata Consultancy Service Limited

Minneapolis, MN • On-site

$120K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 2 days ago

Job description

Must Have Technical/Functional Skills
• AI/ML Program Delivery & Lifecycle Management
• Agile / Scrum Project Management
• Multi-workstream Program Management (enterprise scale)
• Stakeholder Management (Business + IT Leadership)AI/ML & GenAI delivery exposure (LLM, RAG, Agentic AI)
• Financial & Budget Management (SoW, forecasting)
• Risk & Governance Management (RAID, compliance)
• Cross-functional Team Leadership
Roles & Responsibilities
• Lead end-to-end AI workstream delivery (planning execution monitoring
• Manage project plans, timelines, dependencies, resources
• Drive Agile ceremonies (sprint planning, stand-ups, retrospectives)
• Act as primary interface between stakeholders and delivery teams
• Ensure governance, compliance, and responsible AI adherence
• Coordinate across AI engineering, data, architecture, QA teams
• Track KPIs (timeline, quality, business outcomes)
• Manage budgets, forecasts, and vendor coordination
• Identify & mitigate risks, issues, dependencies (RAID)
• Lead cross-functional AI teams and delivery model execution
Salary Range: $120,000- $140,000 a year
TCS Employee Benefits Summary:
Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement.
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
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