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About This Role
Position Title:
AI Engineer Job Group:
Professional & Scientific Required Minimum Qualifications:
High school diploma or equivalent Job Description:
Information Technology Services (ITS) at Iowa State University is seeking an Artificial Intelligence (AI) Engineer (Software Developer I) to support the development, deployment, and maintenance of AI solutions in a higher education research institution. This role is centered on the practical implementation of AI tools and features that support the university’s mission and improve institutional services.
The ideal candidate will have demonstrated experience designing, developing, and implementing enterprise AI solutions using Microsoft technologies and modern cloud platforms. This individual will be skilled in building conversational and autonomous AI agents with Copilot Studio and configuring topics, generative responses, plugins, actions, and knowledge sources to support department-specific business needs. Experience integrating AI solutions with enterprise platforms, such as Salesforce, including live-agent handoff, case creation, custom connectors, and OAuth-based authentication workflows, is highly desirable.
The successful candidate will also possess strong expertise in leveraging Microsoft Azure services and development tools to deliver scalable AI-enabled applications and seamlessly integrate AI capabilities into organizational services and processes. Additional qualifications include experience developing and maintaining complex Power Automate workflows to automate data ingestion, synchronization, and cross-platform business processes.
A strong understanding of AI governance, operational excellence, and security best practices is essential. Candidates should have experience implementing telemetry, monitoring, and security controls across Copilot Studio, Microsoft Foundry, Azure, and the Power Platform, as well as configuring security measures such as rate limiting, API protection, and traffic management through Azure Front Door and Azure API Management (APIM). The ideal candidate will combine technical expertise with a strategic mindset to deliver secure, reliable, and impactful AI solutions that enhance organizational effectiveness and user experiences.
Duties include :
- Collaborate with end users and stakeholders in a higher education, extension, and research environment to gather and document business and technical requirements for AI capabilities.
- Design, develop, test, and maintain AI applications and services using low-code Microsoft tools to meet institutional needs.
- Integrate AI functionality into university systems using the Microsoft technical stack.
- Design and implement multi-agent architecture elements in the Microsoft ecosystem.
- Troubleshoot, debug, and resolve issues in both custom and third-party applications.
- Monitor system health, analyze logs and metrics, and implement fixes as needed.
Maintain secure access patterns, authentication, authorization, and data protection controls for AI applications using the Azure cloud platform.
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This position is part of a new team at Iowa State focused on automation and AI innovation. You’ll work with cutting-edge technologies, help shape the university’s approach to AI implementation, and develop applications used by faculty, students, and staff across campus. It’s a dynamic environment where your work will make a tangible impact.
Preferred Qualifications:
- Bachelor’s degree in computer science, data science, computer engineering, math or related field with a Machine Learning or AI concentration
- Experience developing and maintaining AI-powered applications using Azure AI services, Azure OpenAI, Microsoft Foundry, and Microsoft Copilot technologies.
- Experience integrating Copilot Studio agents with backend services using Power Automate, Azure Functions, APIs, and custom connectors in a large higher education institution
- Experience creating and administering Microsoft Foundry endpoints for AI models with Entra security for authentication and configuring pipelines in Power Platform to manage solution deployments.
Experience designing and implementing API gateways and authentication mechanisms using Microsoft Entra ID, Azure Functions, and Azure Key Vault to provide secure, unified access to AI models hosted on Azure.
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For more information about Information Technology Services, please visit: Information Technology Services
Candidates must be legally authorized to work in the U.S. on an ongoing basis without sponsorship. Immigration sponsorship is not available for this position.
Application Instructions:
To apply for this position, please click on “Apply” and complete the Employment Application. Please be prepared to enter or attach the following:
- Resume/Curriculum Vitae
Letter of Application/Cover Letter *
Why Choose Iowa State University?
Iowa State Employees enjoy comprehensive health and work-life benefits, including medical and dental, as well as:
- Retirement benefits including defined benefit and defined contribution plans
- Generous vacation, holiday, and sick time and leave plans
- Onsite childcare (Ames, Iowa)
- Life insurance and long-term disability
- Flexible Spending Accounts
- Various voluntary benefits and discounts
- Employee Assistance Program
- Wellbeing program
Iowa State offers WorkFlex options for some positions. WorkFlex offers flexibility on when, where, and how you do your work. For more information, please speak with the Hiring Manager. *
If you have questions regarding this application process, please email [email protected], or call 515-294-4800 or Toll Free: 1-877-477-7485.
Appointment Type:
Regular Number of Months Employed Per Year:
12 Month Work Period Time Type:
Full time Pay Grade:
PS808 Original Posting Date:
September 25, 2026 Posting Close Date:
October 1, 2026 Job Requisition Number:
R19976 Iowa State University does not discriminate on the basis of race, color, age, ethnicity, religion, national origin, pregnancy, sexual orientation, genetic information, sex, marital status, disability, or status as a U.S. Veteran. Inquiries regarding non-discrimination policies may be directed to Office of Equal Opportunity, 2680 Beardshear Hall, 515 Morrill Road, Ames, Iowa 50011, Tel. 515-294-7612, email [email protected] .
General ISU compensation information can be found on the University Human Resources website. Please note that this is only a list of ranges and individuals will be paid commensurate with qualifications.
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Iowa State University, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $212,000 based on 11,857 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Iowa State University AI Hiring
Iowa State University has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in IA, US.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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