ZipRecruiter

Log In

1

Internship Retrieval Augmented Generation Jobs in Utah

OmegaHires

Java Developer with AI

Salt Lake City, UT · On-site

$49.25 - $63.75/hr

... RAG (Retrieval-Augmented Generation) solutions using vector databases such as Pinecone, ChromaDB, Weaviate, Milvus, or FAISS. - Experience integrating AI models such as OpenAI GPT, Azure OpenAI ...

New

CardWorks

Director, Data Science

South Jordan, UT · On-site

Develop Retrieval-Augmented Generation (RAG) solutions and AI agents that enable continuous monitoring of competitor activity, customer trends, market signals, and regulatory developments. * Build ...

Awardco

Principal AI Solutions Architect

Lindon, UT · On-site

Architect the retrieval-augmented generation (RAG), Data Graph, GraphRAG layer so LLM responses are grounded in a well defined Ontology with trusted definitions and edges so live operational ...

Packsize

Sr. AI Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

Retrieval-Augmented Generation (RAG) * Multi-agent orchestration * Enterprise integrations (SAP, Salesforce, Databricks, SharePoint, Azure Ecosystem) Guide use-case prioritization and ...

Lucid Software

Sr. Product Manager, AI

Salt Lake City, UT · On-site

$122K - $161K/yr

Strong understanding of modern AI systems, including agent architectures, tool use, retrieval-augmented generation (RAG), AI evaluations, and the tradeoffs between quality, latency, reliability, and ...

Lucid Software

Sr. Product Manager, AI

Salt Lake City, UT · On-site +1

$122K - $161K/yr

Strong understanding of modern AI systems, including agent architectures, tool use, retrieval-augmented generation (RAG), AI evaluations, and the tradeoffs between quality, latency, reliability, and ...

Epicor

Manager of Product Development | AI Platform

Lehi, UT · Hybrid

$107K - $134K/yr

Knowledge of modern artificial intelligence frameworks including retrieval-augmented generation, vector databases, orchestration frameworks, and observability tools * Familiarity with emerging ...

eNett

Senior Backend Engineer - AI Platform

Salt Lake City, UT · On-site +1

$118K - $156K/yr

Design solutions for context management, memory, and retrieval-augmented generation (RAG) to enhance agent effectiveness. Experience you'll bring: * Bachelor's degree in Computer Science or Software ...

Amh

Product Engineering Architect

Draper, UT

Designs and delivers enterprise-grade AI solutions, including Generative AI applications, Agentic AI systems, Retrieval-Augmented Generation (RAG) pipelines, LLM integrations, and MLOps/LLMOps ...

next page

Showing results 1-20

All JobsRetrieval Augmented Generation JobsInternship Retrieval Augmented Generation JobsInternship Retrieval Augmented Generation Jobs in Utah

Internship Retrieval Augmented Generation information

What are the key skills and qualifications needed to thrive as an intern working with Retrieval Augmented Generation (RAG), and why are they important?

To thrive as an intern in Retrieval Augmented Generation, you need a foundational understanding of natural language processing, machine learning concepts, and strong programming skills, often supported by coursework or research in computer science or data science. Familiarity with tools like Python, PyTorch or TensorFlow, and experience with libraries such as Hugging Face Transformers and vector databases are typically required. Strong analytical thinking, curiosity, and effective communication make candidates stand out in collaborative, research-intensive environments. These abilities are critical for developing, evaluating, and improving RAG systems that combine information retrieval with generative models.

What is an Internship in Retrieval Augmented Generation (RAG)?

An Internship in Retrieval Augmented Generation (RAG) is a temporary position, typically for students or early-career professionals, focused on developing or researching AI systems that combine information retrieval with generative models. Interns in this field may work on enhancing how AI models find and use external data sources to generate accurate, context-aware responses. This role often involves tasks such as data preprocessing, implementing retrieval algorithms, fine-tuning language models, and evaluating system performance. It offers valuable hands-on experience with cutting-edge AI technologies and frameworks.

What types of projects or tasks can I expect to work on during an Internship in Retrieval Augmented Generation (RAG)?

As an intern in Retrieval Augmented Generation, you can expect to work on projects that involve integrating information retrieval systems with generative AI models. Typical tasks may include curating and preprocessing data sets, developing or fine-tuning retrieval algorithms, evaluating the performance of RAG pipelines, and collaborating with engineers and researchers to improve end-to-end system accuracy. You may also assist in conducting experiments, analyzing results, and documenting findings, all within a collaborative team environment that values innovation and knowledge sharing.

What is the difference between Internship Retrieval Augmented Generation vs Internship Data Analyst?

AspectInternship Retrieval Augmented GenerationInternship Data Analyst
Required SkillsKnowledge of AI, NLP, retrieval systems, programmingData analysis, statistical skills, Excel, SQL
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing departments
Employer UsageDevelop AI models, improve retrieval systemsAnalyze data trends, generate reports

Internship Retrieval Augmented Generation focuses on developing AI models that combine retrieval systems with language generation, requiring skills in AI and programming. In contrast, an Internship Data Analyst concentrates on analyzing data sets to inform business decisions, emphasizing statistical and analytical skills. Both roles are common in tech and business sectors but serve different functions within organizations.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Utah? The most popular types of Retrieval Augmented Generation jobs in Utah are:
What are popular job titles related to Internship Retrieval Augmented Generation jobs in Utah? For Internship Retrieval Augmented Generation jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Internship Retrieval Augmented Generation jobs in Utah look for? The top searched job categories for Internship Retrieval Augmented Generation jobs in Utah are:
What cities in Utah are hiring for Internship Retrieval Augmented Generation jobs? Cities in Utah with the most Internship Retrieval Augmented Generation job openings:
Internship Retrieval Augmented Generation jobs near you
Applied AI Field Engineer (Orlando)

Applied AI Field Engineer (Orlando)

Trilon Group

Salt Lake City, UT

$155K - $190K/yr

Full-time

Posted 16 days ago

Job description

Description
Trilon is building a supercharged, technology-enabled future for our people and partners. The Applied AI Engineer plays a critical role in that mission by building the AI-powered features that enable our tools to compress real engineering labor across our operating companies. 
This role sits at the intersection of software engineering and applied AI, focused on designing and implementing the intelligence layer of our products. You translate product requirements and architectural patterns into working AI capabilities by building prompt frameworks, retrieval-augmented generation pipelines, and agent-based workflows that operate against real engineering data and deliverables. 
Working within a product pod, you partner closely with the Lead Engineer, Software Engineer, and QA Engineer to deliver production-ready solutions. You own how the system reasons, including prompt design, context management, model integration, and orchestration logic. You also help define how quality is measured for AI outputs, ensuring tools are accurate, reliable, and usable in real-world workflows. 
You will engage directly with engineers across our operating companies to understand workflows, validate solutions, and iterate quickly based on feedback. You may also participate in field-based project hackathons, embedding with teams to identify high-impact opportunities and rapidly prototype solutions that inform platform development. 
This role requires strong software engineering fundamentals, deep hands-on experience with modern AI tooling, and the ability to operate in a fast-moving environment where both the technology and the product are evolving. You are comfortable with ambiguity, rigorous about output quality, and focused on delivering AI that engineers trust and use. 

Key Responsibilities
AI Application Development
  • Design and build AI-powered features using large language models and related tooling 
  • Develop and maintain prompt architectures that drive consistent, high-quality outputs 
  • Implement retrieval-augmented generation pipelines using enterprise data sources 
  • Build and orchestrate agent-based workflows to automate targeted tasks 
Model Integration and System Behavior 
  • Integrate LLM APIs such as Anthropic Claude and OpenAI into production systems 
  • Design context management strategies to ensure outputs are grounded, relevant, and accurate 
  • Manage tradeoffs across latency, cost, and performance in AI workflows 
  • Continuously improve system behavior through prompt iteration and architecture refinement
Pod Collaboration and Delivery 
  • Partner with Software Engineers to integrate AI capabilities into applications, APIs, and user interfaces 
  • Align with the Lead Engineer on technical direction, architecture, and implementation decisions 
  • Work with QA Engineers to define evaluation criteria, testing strategies, and quality thresholds for AI outputs 
  • Translate product requirements into scalable, production-ready AI solutions 
Evaluation and Quality Optimization 
  • Define and implement approaches for evaluating non-deterministic AI outputs 
  • Build test cases, benchmarks, and evaluation pipelines to track output quality over time 
  • Identify failure modes and iterate on prompts, pipelines, and orchestration logic 
  • Ensure consistency and reliability as models, prompts, and data sources evolve 
Continuous Improvement and Innovation 
  • Stay current with advancements in LLMs, vector databases, and agent frameworks 
  • Experiment with new tools and techniques to improve speed, quality, and capability 
  • Contribute reusable patterns, components, and best practices across pods 


Skills, Knowledge and Expertise
  • 4+ years of experience in software engineering, applied AI, or machine learning development 
  • Strong programming skills in Python and/or JavaScript 
  • Hands-on experience working with LLM APIs such as Anthropic Claude, OpenAI, or similar 
  • Experience designing and implementing prompt architectures and prompt engineering techniques 
  • Experience building retrieval-augmented generation pipelines and working with vector databases 
  • Familiarity with agent orchestration frameworks and multi-step AI workflows 
  • Experience integrating AI capabilities into applications via APIs and backend systems 
  • Strong understanding of handling structured and unstructured data in AI systems 
  • Ability to evaluate, debug, and improve non-deterministic AI outputs 
  • Experience working in a fast-paced, product-oriented development environment 
  • Strong problem-solving skills and ability to operate in ambiguous, evolving contexts 
  • Ability to collaborate closely with engineers, product managers, and QA within a pod structure 
  • Excellent communication skills and ability to explain technical concepts clearly 
  • Curiosity and willingness to learn domain-specific workflows, particularly within engineering and AEC contexts