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Ai Rag Jobs in Rochester, MN (NOW HIRING)

Da Vinci Software

AI Developer

Rochester, MN · On-site +1

AI/ML Fluency: Strong understanding of the lifecycle of LLMs and autonomous agents, including inference optimization and RAG architectures. * Operational Rigor: A track record of implementing ...

New

Apex Systems

Software Engineer

Rochester, MN · On-site

Ensure the performance, scalability, and reliability of AI-driven data systems. Required ... Experience with vector databases, embeddings, or RAG architectures. * Familiarity with CI/CD and ...

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Ai Rag information

See Rochester, MN salary details

$32.5K

$59.2K

$84.9K

How much do ai rag jobs pay per year?

As of Jul 15, 2026, the average yearly pay for ai rag in Rochester, MN is $59,206.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,800.00 and $66,100.00 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.

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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Ai Rag jobs near you
AI Developer

AI Developer

Da Vinci Software

Rochester, MN • On-site, Remote

Contractor

This job post has expired today. Applications are no longer accepted.

Job description

Overview:
Our client is seeking an AI Developer.  As a Senior Software Engineer for AI Platform Engineering, you will bridge the gap between high-scale system architecture and frontier AI.  You will be one of builders of our Model & Agent Runtimes—the specialized engines that govern how models and autonomous agents execute across our hybrid-cloud footprint. This isn't just about deployment; it’s about a platform-first mindset.
Core responsibilities:
  • You will ensure that AI capabilities are scalable, secure, and governed through world-class AgentOps, LLMOps, and MLOps practices.
  • What You’ll Do Architect the Future of Runtimes: Design and implement high-performance hosting environments for both specialized models and autonomous agents.
  • Scale Hybrid-Cloud Infrastructure: Build multi-tenant platform capabilities that support seamless agent and model execution across diverse cloud and on-prem environments.
  • Drive Operational Excellence: Implement robust solutions for real-time monitoring, distributed tracing, and automated evaluation of agents & models in production.
  • Operational Stewardship: Act as a member of our rotational platform operational team, ensuring the reliability and uptime of critical AI services.
  • Collaborate & Advocate: Partner with cross-functional AI teams to identify system friction, streamlining their workflows and accelerating the delivery of AI-driven value.
Education:
  • Bachelor's Degree in Computer Science/Engineering or related field with 5 years of experience as noted below; OR an Associate's degree in Computer/Science/Engineering or related field with 7 years of experience.
  • Have in-depth knowledge of software engineering with experience coding applications or services in a high-level language (C, C++, Golang, Java, C# etc.) and a basic knowledge of related fields.
  • Demonstrated problem solving and time management skills.
  • Possesses strong technical aptitude for designing and implementing software solutions.
  • Experience with modern application development frameworks
  • Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
  • Deep hands-on technical expertise, excellent verbal and written communication skills.
  • Experience with Agile software development techniques.

Required Skills:
  • Deep Systems Expertise: Proven experience building scalable back-end systems, ideally with a focus on containerization and orchestration (4+ years of in-depth Kubernetes is a must).
  • AI/ML Fluency: Strong understanding of the lifecycle of LLMs and autonomous agents, including inference optimization and RAG architectures.
  • Operational Rigor: A track record of implementing observability (logging, metrics, tracing) in complex, distributed environments.
  • Problem-Solving Mindset: The ability to turn abstract AI research into production-grade, hardened platform features.
  • Have in-depth knowledge of software engineering with experience coding applications or services in a high-level programming language, preferably Python, and a basic knowledge of related fields.
  • Demonstrated problem solving and time management skills.
  • Possesses strong technical aptitude for designing and implementing software solutions.
  • Experience with modern application development frameworks
  • Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
  • Deep hands-on technical expertise, excellent verbal and written communication skills.
  • Experience with Agile software development techniques.
  • Pro Desk API
Preferred Qualifications:
  • Ability to use a wide variety of open-source technologies and cloud-based services.
  • Experience writing software for hybrid cloud (GCP, AWS, Azure).
  • Experience building high-performance, highly available and scalable distributed systems.
  • Experience developing software for healthcare related industries.
Additional Information:
  • Fully Remote Role
  • Contract position
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About Da Vinci Software

Sourced by ZipRecruiter

Who We Are We are a software company that strives to build sustainable relationships through the delivery of innovative solutions. Agile software development is at the heart of 'how we work' which allows us to bring people together for strong collaboration and problem solving. What We Do We provide enterprise-level agile coaching and development services. The Da Vinci Agile Coaching model is built on four pillars that ensure successful adoption and scale across an organization. The enterprise framework we have built supports this foundation through recognition of, and integration with, legacy processes. We passionately believe 'how we work' is the intangible our developers demonstrate for our clients every day. Our high-performing team members provide leadership and chemistry on your teams. We provide architects, developers and testers that enjoy accountability, team success and delivering meaningful products.

Industry

It services

Company size

11 - 50 Employees

Headquarters location

Burnsville, MN, US

Year founded

2008

Social media

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