AI Research Engineer Jobs in Utah
AI Research Engineer jobs in Utah are concentrated in Salt Lake City, Provo, and Lehi, where a dense corridor of technology companies and research institutions drives consistent demand for professionals specializing in machine learning systems, natural language processing, and computer vision. Employers such as Adobe, Qualtrics, and the University of Utah regularly hire at levels from associate researcher to principal engineer. The Wasatch Front has emerged as one of the more active markets for applied AI research outside the traditional coastal hubs. See the openings below and apply to the ones that match your experience.
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At NiCE, we don't limit our challenges. We challenge our limits. Always. We're ambitious. We're game changers. And we play to win. We set the highest standards and execute beyond them. And if you're like us, we can offer you the ultimate career opportunity that will light a fire within you.
Principal AI Software Engineer – Cloud AI Platforms
At NICE, we are not just building software—we are transforming how cloud operations are run using AI. We are building intelligent platforms that can understand system behavior, make decisions, and automate real-world operational workflows at scale. If you're excited about applying AI beyond chatbots into real production systems, this is an opportunity to work on meaningful, high-impact problems.
What's the role all about?
As an AI Software Engineer, you will be part of a team building AI-powered operational platforms that integrate across monitoring systems, CI/CD pipelines, ticketing tools, and cloud infrastructure. You will work on designing and implementing intelligent workflows, integrating AI models, and building scalable systems that automate complex operational tasks.
This is a highly hands-on role focused on building, integrating, and scaling AI-driven solutions in production environments.
How will you make an impact?
- Build and scale AI-driven workflows and automation systems
- Develop integrations with systems like monitoring platforms, ticketing tools (ServiceNow, Jira, OpsGenie), CI/CD pipelines, and cloud services
- Design and implement APIs, tools, and data pipelines that power AI-driven decision-making
- 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 applications using TypeScript, React, and Next.js — from user dashboards and personalized experiences to real-time analytics and interactive tools
- Translate real-world operational problems into automated, intelligent solutions
- Collaborate with Product, SRE, and Infrastructure teams to deliver end-to-end capabilities
- Improve system performance, reliability, and observability
- Build evaluation and observability systems — measure model capabilities, monitor output quality, and create dashboards that keep the product improvable
- Create reusable platforms and tools that accelerate development — component libraries, shared abstractions, internal tooling that multiplies team productivity
Key Responsibilities
- Design and develop scalable backend systems for AI-powered platforms
- Build and maintain AI integrations, workflows, and automation pipelines
- Implement REST APIs, microservices, and event-driven architectures
- Design and implement database schemas and queries for complex domains — tracking, engagement, reporting
- Work with both structured and unstructured data for AI use cases
- Contribute to CI/CD pipelines, testing, and deployment automation
- Troubleshoot and optimize production systems
- Collaborate with cross-functional teams to deliver high-quality solutions
- Contribute to reusable frameworks and engineering best practices
- Prototype fast — move from concept to working demo in days, ship incrementally
What we're looking for
- 10+ years of software engineering experience, strong focus on full-stack web development
- Expert in TypeScript and React — performance optimization, modern patterns (hooks, context, suspense), component architecture
- Production experience with Next.js — App Router, Server Components, API routes, SSR/SSG, edge deployment
- Hands-on experience with LLMs — prompt engineering, streaming APIs, function calling, tool-use, chaining and orchestration patterns
- Experience with Vercel AI SDK — unified LLM provider interface, streaming, structured output, tool calling across OpenAI/Anthropic/Google/xAI
- Model Context Protocol (MCP) — building or consuming MCP servers for extensible AI tool use
- Strong backend fundamentals — Node.js or Python, REST/GraphQL APIs, relational databases, Redis, auth
- Solid database design — PostgreSQL, Drizzle ORM, schema modeling for complex domains, query optimization, migrations
- Experience building scalable, distributed systems in cloud environments (AWS / Azure)
- Working knowledge of CI/CD, Docker, Kubernetes
- Familiarity with Tailwind CSS, Radix UI and modern component-driven UI development
- High agency — you operate independently in ambiguous environments, take ownership of problems, and drive them to completion
- Strong problem-solving and analytical skills
- Ability to work in a fast-paced, evolving environment
- Communicate effectively with both technical and non-technical stakeholders
Nice to have
- Experience building agentic coding tools, AI agent frameworks, or developer-facing SDKs/APIs (Claude Agent SDK, OpenAI Agents SDK)
- Experience with Vercel ecosystem — Next.js, AI SDK providers, Turbopack
- Background in evaluation frameworks — measuring model capabilities, collecting human feedback at scale, A/B testing outputs
- Experience with sandboxed execution environments for safely running AI-generated code
- Built research tools, experimentation platforms, or scientific software
- Proficiency with Python — FastAPI/Django, data pipelines, ML tooling
- Knowledge of observability tools (Grafana, Prometheus, Sentry, etc.)
- Experience building automation or internal platforms
- Familiarity with real-time features — WebSockets, streaming UX, collaborative interfaces
- Knowledge of advanced web technologies — WebGL, WebAssembly, web workers, PWAs
- Experience with alternate JS runtimes — Bun, Deno
- Built open-source tools or platforms with active user communities
- Strong quantitative foundation (math, physics, or related fields)
Representative Projects
Things you might build in this role:
- Interfaces for collecting and managing human feedback on model outputs at scale
- Experiment orchestration platforms — launch, monitor, and analyze complex AI research runs
- Visualization tools that help understand model behavior and identify failure modes
- Reusable components and frameworks that enable rapid development of new AI applications
- Sandboxed execution environments for safely running AI-generated code
- AI-powered personalization engines — tutoring, content generation, adaptive features
- Workflow builders that let non-engineers orchestrate AI capabilities visually
- Enterprise integrations — ServiceNow, Salesforce, Confluence, Jira
About NiCE
NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions.
Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries.
NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.
At NiCE, we don't limit our challenges. We challenge our limits. Always. We're ambitious. We're game changers. And we play to win. We set the highest standards and execute beyond them. And if you're like us, we can offer you the ultimate career opportunity that will light a fire within you.
Principal AI Software Engineer – Cloud AI Platforms
At NICE, we are not just building software—we are transforming how cloud operations are run using AI. We are building intelligent platforms that can understand system behavior, make decisions, and automate real-world operational workflows at scale. If you're excited about applying AI beyond chatbots into real production systems, this is an opportunity to work on meaningful, high-impact problems.
What's the role all about?
As an AI Software Engineer, you will be part of a team building AI-powered operational platforms that integrate across monitoring systems, CI/CD pipelines, ticketing tools, and cloud infrastructure. You will work on designing and implementing intelligent workflows, integrating AI models, and building scalable systems that automate complex operational tasks.
This is a highly hands-on role focused on building, integrating, and scaling AI-driven solutions in production environments.
How will you make an impact?
- Build and scale AI-driven workflows and automation systems
- Develop integrations with systems like monitoring platforms, ticketing tools (ServiceNow, Jira, OpsGenie), CI/CD pipelines, and cloud services
- Design and implement APIs, tools, and data pipelines that power AI-driven decision-making
- 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 applications using TypeScript, React, and Next.js — from user dashboards and personalized experiences to real-time analytics and interactive tools
- Translate real-world operational problems into automated, intelligent solutions
- Collaborate with Product, SRE, and Infrastructure teams to deliver end-to-end capabilities
- Improve system performance, reliability, and observability
- Build evaluation and observability systems — measure model capabilities, monitor output quality, and create dashboards that keep the product improvable
- Create reusable platforms and tools that accelerate development — component libraries, shared abstractions, internal tooling that multiplies team productivity
Key Responsibilities
- Design and develop scalable backend systems for AI-powered platforms
- Build and maintain AI integrations, workflows, and automation pipelines
- Implement REST APIs, microservices, and event-driven architectures
- Design and implement database schemas and queries for complex domains — tracking, engagement, reporting
- Work with both structured and unstructured data for AI use cases
- Contribute to CI/CD pipelines, testing, and deployment automation
- Troubleshoot and optimize production systems
- Collaborate with cross-functional teams to deliver high-quality solutions
- Contribute to reusable frameworks and engineering best practices
- Prototype fast — move from concept to working demo in days, ship incrementally
What we're looking for
- 10+ years of software engineering experience, strong focus on full-stack web development
- Expert in TypeScript and React — performance optimization, modern patterns (hooks, context, suspense), component architecture
- Production experience with Next.js — App Router, Server Components, API routes, SSR/SSG, edge deployment
- Hands-on experience with LLMs — prompt engineering, streaming APIs, function calling, tool-use, chaining and orchestration patterns
- Experience with Vercel AI SDK — unified LLM provider interface, streaming, structured output, tool calling across OpenAI/Anthropic/Google/xAI
- Model Context Protocol (MCP) — building or consuming MCP servers for extensible AI tool use
- Strong backend fundamentals — Node.js or Python, REST/GraphQL APIs, relational databases, Redis, auth
- Solid database design — PostgreSQL, Drizzle ORM, schema modeling for complex domains, query optimization, migrations
- Experience building scalable, distributed systems in cloud environments (AWS / Azure)
- Working knowledge of CI/CD, Docker, Kubernetes
- Familiarity with Tailwind CSS, Radix UI and modern component-driven UI development
- High agency — you operate independently in ambiguous environments, take ownership of problems, and drive them to completion
- Strong problem-solving and analytical skills
- Ability to work in a fast-paced, evolving environment
- Communicate effectively with both technical and non-technical stakeholders
Nice to have
- Experience building agentic coding tools, AI agent frameworks, or developer-facing SDKs/APIs (Claude Agent SDK, OpenAI Agents SDK)
- Experience with Vercel ecosystem — Next.js, AI SDK providers, Turbopack
- Background in evaluation frameworks — measuring model capabilities, collecting human feedback at scale, A/B testing outputs
- Experience with sandboxed execution environments for safely running AI-generated code
- Built research tools, experimentation platforms, or scientific software
- Proficiency with Python — FastAPI/Django, data pipelines, ML tooling
- Knowledge of observability tools (Grafana, Prometheus, Sentry, etc.)
- Experience building automation or internal platforms
- Familiarity with real-time features — WebSockets, streaming UX, collaborative interfaces
- Knowledge of advanced web technologies — WebGL, WebAssembly, web workers, PWAs
- Experience with alternate JS runtimes — Bun, Deno
- Built open-source tools or platforms with active user communities
- Strong quantitative foundation (math, physics, or related fields)
Representative Projects
Things you might build in this role:
- Interfaces for collecting and managing human feedback on model outputs at scale
- Experiment orchestration platforms — launch, monitor, and analyze complex AI research runs
- Visualization tools that help understand model behavior and identify failure modes
- Reusable components and frameworks that enable rapid development of new AI applications
- Sandboxed execution environments for safely running AI-generated code
- AI-powered personalization engines — tutoring, content generation, adaptive features
- Workflow builders that let non-engineers orchestrate AI capabilities visually
- Enterprise integrations — ServiceNow, Salesforce, Confluence, Jira
About NiCE
NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions.
Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries.
NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.
See All 51 AI Research Engineer Jobs in Utah
Find roles in Utah that match your experience and apply in just a few clicks.
Find AI Research Engineer JobsAI Research Engineer Jobs by City in Utah
Where Utah roles are concentrated, by current openings.
AI Research Engineer Job Market in Utah
A snapshot from current Utah openings, updated as new roles post.
Who's Hiring
- Atonom5A
- CVS Health4
- Utah State University4
- Western Governors University3
- Packsize2
Top Industries Hiring
- Technology & Software6
- Education5
- Healthcare & Medical Services4
- Insurance2
- Banking & Financial Services2
What Utah Employers Look For
The qualifications that appear most often in AI research engineer jobs across Utah.
- Master's or PhD in computer science, machine learning, or a closely related field
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience designing and training large-scale models for production environments
- Demonstrated publication record or open-source contributions in an AI subfield
- Ability to collaborate cross-functionally with product and software engineering teams
- Familiarity with cloud infrastructure such as AWS, Azure, or Google Cloud for model deployment
AI Research Engineer Jobs in Utah: Frequently Asked Questions
How do you become a ai research engineer in Utah?
The most direct path is earning at least a bachelor's degree in computer science, mathematics, or a related discipline, though most competitive roles in Utah prefer a master's or PhD with a research focus. Utah does not require a state-issued license for this role. Candidates strengthen their applications by completing graduate research, contributing to published work, and building a portfolio of projects in machine learning, NLP, or computer vision before applying to positions at Utah's technology and research institutions.
How much do AI research engineers make in Utah?
AI research engineers in Utah earn a median of about $94,700 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $72,990 for the lowest 10% to over $169,890 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai research engineers in Utah?
Companies currently hiring ai research engineers in Utah include Atonom, CVS Health, and Utah State University, per current listings on Migrate Mate as of July 2026. Utah's technology corridor along the Wasatch Front, sometimes called Silicon Slopes, also draws hiring from enterprise software firms, defense contractors, and university-affiliated research labs based in the region.
Which Utah cities have the most ai research engineer jobs?
Salt Lake City, Lehi, and Provo account for the highest concentration of ai research engineer openings in Utah. Salt Lake City anchors the market through its mix of corporate headquarters, university research, and healthcare technology companies, while Provo and Lehi benefit from the dense cluster of high-growth software and data companies that have established major operations along the Interstate 15 technology corridor.
Are there remote ai research engineer jobs in Utah?
Yes, and more than most fields. About 45% of ai research engineer openings tied to Utah are remote or hybrid as of July 2026, reflecting the desk-based and computational nature of most research work. The portions of the role most commonly offered remotely include model development, experimentation, and literature review, while on-site expectations tend to apply to collaborative prototyping and hardware-dependent research.
How can I get hired as a ai research engineer in Utah with little or no experience?
The most realistic entry path is securing a graduate research assistantship or internship at the University of Utah or Brigham Young University, both of which have active AI and machine learning labs that feed directly into Utah employer pipelines. Candidates without formal experience can also target associate machine learning engineer or data scientist roles at Utah technology companies, then transition into research functions. A strong GitHub portfolio demonstrating model-building projects and a record of coursework in deep learning or statistical inference significantly improves early-career candidacy.
Where can I find and apply to ai research engineer jobs in Utah?
You can find and apply to ai research engineer jobs in Utah on Migrate Mate, which lists current openings tied to the state. Search the available roles, identify the ones that match your background and specialization, and apply directly to the positions that fit. No account creation is required to view and apply to the openings listed.
See All 51 AI Research Engineer Jobs in Utah
Find roles in Utah that match your experience and apply in just a few clicks.
Find AI Research Engineer Jobs