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Ai Rag Jobs in Utah (NOW HIRING)

D.A. Davidson

AI & Automation Engineer

Salt Lake City, UT · On-site

... RAG) pipelines with vector databases for domain-specific Q&A. Experience with Azure AI Foundry and ... Azure AI capabilities like document intelligence, computer vision, speech, and more. • Financial ...

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Wsgr

Senior AI Security Engineer

Salt Lake City, UT · On-site +1

$110K - $151K/yr

The Senior AI Security Engineer, under the direction of the Director, Security Engineering and ... generation (RAG) pipelines, and MCP server deployments across firm systems * Lead security ...

NICE

Senior AI Software Engineer

Sandy, UT · On-site

$116K - $153K/yr

Work on LLM integrations, prompt engineering, and orchestration layers - streaming responses, function calling, tool use, RAG pipelines, agentic orchestration * Build and maintain full-stack AI ...

NICE

Principal AI Software Engineer

Seattle, WA · On-site

$153K - $206K/yr

Work on LLM integrations, prompt engineering, and orchestration layers - streaming responses, function calling, tool use, RAG pipelines, agentic orchestration * Build and maintain full-stack AI ...

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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 Utah look for? The top searched job categories for Ai Rag jobs in Utah are:
What cities in Utah are hiring for Ai Rag jobs? Cities in Utah with the most Ai Rag job openings:
Ai Rag jobs near you

Senior Software Engineer, Agentic Systems

NVIDIA AI

Santa Clara, UT • On-site

$109K - $144K/yr

Full-time

Posted 6 days ago

Job description

Job Summary:
NVIDIA AI is looking for a Senior Software Engineer to help build the NeMo Platform, a product for developing and operating AI systems at scale. The role involves designing APIs, building systems for evaluating AI agents, and collaborating with various teams to enhance agentic capabilities.
Responsibilities:
• Design and implement Python-first APIs, SDK workflows, and plugin interfaces for building, measuring, and improving agents across multiple runtimes and product surfaces
• Build reusable systems for observing behavior, measuring progress, detecting regressions, and turning runtime evidence into product decisions
• Build systems for ingesting, normalizing, validating, and analyzing agent execution data and evaluation datasets
• Partner with research, product, platform, and infrastructure teams to integrate agentic capabilities broadly across NVIDIA agent runtimes and developer workflows
• Help turn emerging agent development and improvement techniques into reliable, reusable product capabilities
• Improve reliability, observability, debuggability, and performance across NeMo Platform, SDKs, plugins, jobs, and developer workflows
• Build strong test coverage across unit, integration, E2E, Docker, and Kubernetes workflows
• Drive “speed of light” engineering: fast iteration, high ownership, pragmatic decisions, and performance-minded implementation under production constraints
• Provide senior technical leadership through design reviews, code reviews, mentoring, and ownership of ambiguous cross-component problems
Qualifications:
Required:
• BS, MS, or equivalent experience in Computer Science, Computer Engineering, or a related technical field
• 5+ years of professional software engineering experience building production systems
• Excellent Python engineering skills, including API design, typing, testing, debugging, performance analysis, and maintainable software design
• Experience designing SDKs, libraries, plugins, CLIs, or other developer-facing interfaces
• Experience with distributed systems, cloud-native services, containers, Kubernetes, or job orchestration
• Strong understanding of reliability, scalability, security, and performance tradeoffs in production infrastructure
• Experience with structured data modeling and validation systems such as Pydantic, typed schemas, event/trace models, or SDK-generated types
• Ability to work independently, define technical scope, break down ambiguous problems, and drive work across team boundaries
• Clear communication skills and a track record of collaborating with engineering, product, research, or customer-facing teams
Preferred:
• Experience building, deploying, and iterating on production agentic AI systems where evaluation was used to measure and improve real product outcomes
• Experience designing evaluation workflows for heterogeneous agents, including tool-using agents, RAG agents, workflow agents, coding agents, or long-running autonomous systems
• Experience integrating evaluation capabilities across multiple products, runtimes, or internal platforms, especially through Python SDKs, plugins, or shared developer tooling
• Strong ability to connect technical evaluation work to business outcomes, product quality, user experience, reliability, or operational efficiency
• Experience with enterprise AI systems where measurement, regression testing, observability, governance, and continuous improvement are required for production deployment
Company:
Explore the latest breakthroughs made possible with AI. Founded in , the company is headquartered in Santa Clara, CA, US, , with a team of 10001+ employees. The company is currently Late Stage.

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