1

Retrieval Augmented Generation Jobs in Utah (NOW HIRING)

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 ...

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 ...

Develop innovative AI/ML software solutions, specifically focusing on Generative AI, LLMs, and RAG (Retrieval-Augmented Generation) architectures, while adhering to enterprise software standards.

Work with both structured and unstructured data, including integration with relational databases and vector databases for retrieval augmented generation (RAG). * Communicate effectively with both ...

Sr. Data Engineer

Draper, UT

$107K - $128K/yr

Build and integrate AI-powered applications and agentic workflows (e.g., LLM-based agents, retrieval-augmented generation systems, workflow automation agents) * Design and implement data pipelines ...

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database. * Language Model (LM) Development & Fine-tuning: * Research, select ...

Senior ML Engineer

Lehi, UT

$98K - $134K/yr

Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database. * Language Model (LM) Development & Fine-tuning: * Research, select ...

Senior AI Security Engineer

Salt Lake City, UT · On-site +1

$110K - $151K/yr

Collaborate on designing secure-by-default patterns for LLM integration, agentic workflows, retrieval-augmented generation (RAG) pipelines, and MCP server deployments across firm systems * Lead ...

Senior ML Engineer

Lehi, UT · On-site

$98K - $134K/yr

Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database. * Language Model (LM) Development & Fine-tuning: * Research, select ...

next page

Showing results 1-20

Retrieval Augmented Generation information

What are the typical daily responsibilities of a Retrieval Augmented Generation engineer?

A Retrieval Augmented Generation engineer typically spends their day designing and implementing systems that combine information retrieval with advanced generative models, such as large language models. This includes fine-tuning models, integrating external data sources, developing vector search pipelines, and evaluating output quality. Collaboration with data scientists, machine learning engineers, and product teams is common to ensure the solutions meet user requirements and scale effectively. Additionally, RAG engineers often troubleshoot issues, monitor model performance in production, and stay informed about the latest advancements in AI and information retrieval.

What is a Retrieval Augmented Generation job?

A Retrieval Augmented Generation (RAG) job typically involves developing and optimizing AI systems that enhance text generation by incorporating external knowledge retrieved from relevant sources. Professionals in this field work on integrating retrieval mechanisms with large language models to improve the relevance, accuracy, and factual grounding of generated content. Common responsibilities include designing retrieval systems, fine-tuning language models, optimizing performance, and ensuring the seamless integration of factual data into AI-generated text. This role is highly interdisciplinary, involving expertise in natural language processing (NLP), machine learning, and information retrieval.

What are the key skills and qualifications needed to thrive in the Retrieval Augmented Generation position, and why are they important?

To thrive in a Retrieval Augmented Generation (RAG) engineering role, you need a solid background in machine learning, natural language processing (NLP), and experience with scalable information retrieval systems, typically supported by a relevant degree in computer science or a related field. Familiarity with tools such as Python, PyTorch or TensorFlow, vector databases, and search platforms like Elasticsearch is essential, along with practical experience deploying and tuning RAG pipelines. Strong problem-solving skills, a collaborative mindset, and effective communication abilities set outstanding professionals apart in this field. These competencies are crucial for designing, implementing, and optimizing hybrid retrieval-generation AI systems that address complex, real-world information needs.

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 Retrieval Augmented Generation jobs in Utah? For Retrieval Augmented Generation jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Retrieval Augmented Generation jobs in Utah look for? The top searched job categories for Retrieval Augmented Generation jobs in Utah are:
What cities in Utah are hiring for Retrieval Augmented Generation jobs? Cities in Utah with the most Retrieval Augmented Generation job openings:
Infographic showing various Retrieval Augmented Generation job openings in Utah as of June 2026, with employment types broken down into 36% Full Time, and 64% Part Time. Highlights an 66% Physical, 2% Hybrid, and 32% Remote job distribution.
Software Engineer 2 - AI Platform

Software Engineer 2 - AI Platform

WEX

Salt Lake City, UT • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 20 days ago


WEX Inc. rating

7.3

Company rating: 7.3 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

14th of 20 rated payment service providers


Job description

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Boston, MA; San Francisco Bay Area, CA; Dallas, TX; Salt Lake City, UT; Seattle, WA; and Portland, MEAbout the Team/Role

We are seeking a Software Engineer in the North America Mobility organization. This role will sit in the Platform team that focuses on building AI Platform to support the feature development team to build robust features faster. You will contribute to the architecting and realization of our next-generation Agentic AI Platform. Within this capacity, you will be responsible for the design, development, and deployment of autonomous AI agents, skills, MCP servers, AI tools engineered for advanced reasoning, strategic planning, and the orchestration of intricate financial and operational workflows. Operating at the vanguard of generative AI, distributed systems, and fintech, you will empower WEX to deliver highly intelligent, proactive solutions to an expansive global user base.

Our Platform team is dedicated to architecting scalable, robust, and maintainable UI and API platform solutions that empower internal feature development teams to build at velocity. Within the NAM Mobility ecosystem, our products facilitate strategic credit issuance to fleet organizations and their workforce through WEX-branded or co-branded credit instruments, accepted across a vast network of fueling stations and merchant partners. We provide fleet managers and operators with advanced spend orchestration capabilities, encompassing fuel discounts and sophisticated spend controls that permit precise configuration of merchant restrictions, transaction limits, and velocity thresholds to optimize operational efficiency.

How you'll make an impact:
  • Design, develop, and maintain robust, scalable, and high-performance object oriented code in our backend services.

  • Develop public REST APIs using Java and internal gRPC APIs for inter-service and inter-system communication.

  • Craft systems designs, lead design decisions, and drive alignment with other senior engineers.

  • Write automated unit tests, integration tests, end-to-end tests, concurrency tests, load/performance tests.

  • Analyze existing systems to identify bottlenecks, tech debt, and implement scalability, and stability improvements.

  • Implement automation for testing, monitoring, healing, and scaling applications, continuous integration and deployment to reduce time to market.

  • Collaborate with cross-functional teams, including product managers, designers, and other engineers, to define and implement new features.

  • Conduct code reviews (comment, approve, seek revisions, merge), mentor junior and mid-level engineers, and actively promote engineering best practices.

  • Dive deep and troubleshoot complex issues, devise fixes, author root cause analysis documents, and ensure lasting performance and reliability.

  • Conduct objective and comparative analyses of competing technologies to advise the team of pros and cons of a technology solution.

  • Maintain robust documentation (design docs, run books, change management docs, and readiness plans).

  • Provide live-site support for production applications by monitoring systems, ensuring rapid incident resolution, and driving continuous improvement.

  • Drive cross-team projects as a single-threaded-owner (STO) or tech lead, and actively unblock other engineers to make progress.

Agentic AI & Intelligent Systems :

  • Design and build agentic AI systems and services, enabling autonomous workflows, reasoning, and task execution within Mobility platforms.

  • Develop AI agents from scratch, including orchestration, tool usage, memory, and multi-step decision-making capabilities.

  • Implement and scale multi-agent architectures to support complex, distributed use cases across payments and fleet ecosystems.

  • Integrate systems using Model Context Protocol (MCP) or similar frameworks to enable secure and scalable interaction between AI agents, APIs, and enterprise data sources.

  • Build and optimize LLM-powered services (e.g., OpenAI APIs, LangChain) for production-grade performance, reliability, and cost efficiency.

  • Implement evaluation frameworks, observability, and guardrails to ensure correctness, safety, and compliance of AI-driven systems.

  • 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 Engineering

  • 2-5 years of professional experience in software engineering

  • Strong understanding of data structures and algorithms, object-oriented design, and problem-solving skills

  • Expertise in designing and developing internet-scale services with scalability, availability, security, and reliability design tenets

  • Excellent written and verbal communication skills, and a collaborative and empathetic mindset

  • Proficiency in backend development, with expertise in Java or C#, frameworks like SpringBoot, building and optimizing RESTful APIs, ODATA framework, and SQL

Agentic AI & MCP Experience:

  • Hands-on experience building or contributing to AI/LLM-powered applications or agent-based systems

  • Familiarity with agent frameworks, tool-use patterns, and orchestration of LLM workflows

  • Experience integrating AI systems with external tools/APIs using MCP or similar protocols

  • Understanding of prompt engineering, embeddings, and vector-based retrieval systems

  • Experience designing systems for scaling AI workloads in production environments

Preferred Qualifications
  • Master's degree in computer science or software engineering

  • 3+ years of experience in software engineering

  • Experience with Python, Java, event-driven architecture and tools like Kafka

  • Experience working on card payments

  • Familiarity with cloud-native architecture (containerization using tools such as Docker and Kubernetes)

  • Awareness of API security and PCI DSS compliance requirements

  • Ability to work on existing codebase, contribute improvements, and adapt to legacy systems' constraints

Nice to Have (AI Focus):

  • Experience building AI skills & deploying AI solutions to production environments

  • Experience building production-grade AI agents or copilots

  • Familiarity with multi-agent systems and distributed AI architectures

  • Experience with vector databases (e.g., Pinecone, Weaviate, OpenSearch, Milvus)

  • Knowledge of AI evaluation techniques, safety practices, and responsible AI principles

The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section.Pay Range: $96,100.00 - $115,500.00

What WEX Inc. employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom