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About This Role
Posting Close Date
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Applicants must submit their completed application by 08\-02\-2026 at 11:59 p.m. MSTApplication and Special Instructions
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As part of the application process, all applicants are required to submit a chronological resume. Applications submitted without a chronological resume will be considered incomplete and will not receive further consideration.
This position is based on\-site at a City of Tucson facility. Remote or hybrid work arrangements are not available at this time.
Applicants who meet the minimum qualifications may be evaluated and scored based on their relevant education, experience, and training, as outlined in the job bulletin. The highest\-scoring applicants will be invited to participate in a virtual interview via Microsoft Teams.
IMPORTANT INFORMATION
Virtual interviews are tentatively scheduled for the week of August 17, 2026, and will be conducted via Microsoft Teams (available as a free download).
Hiring interviews, if applicable, may be conducted on\-site at the City of Tucson Information Technology Department in Tucson, Arizona.
The City of Tucson does not provide visa sponsorship. Candidates must be legally authorized to work in the United States at the time of application and throughout the duration of employment.
Relocation expenses will not be be provided for this position. Candidates are responsible for all costs associated with relocating to the Tucson area, if applicable.
Candidates who are placed on the Civil Service Eligibility List and receive a contingent offer of employment must successfully complete the following:
An extensive background investigation, including local, state, and national criminal history and fingerprint checks.
Recruiter Contact Information:
If you have any questions regarding this recruitment, please contact:
Liliana Almeraz
(520\) 837\-4303
[email protected]Position Specific Summary
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The Artificial Intelligence (AI) Systems Engineer at the City of Tucson’s Information Technology (IT) Department is responsible for the design, development, implementation, administration, and maintenance of artificial intelligence solutions that support organizational goals and business operations. This position collaborates with cross\-functional teams to develop, enhance, and support AI\-driven applications and systems, ensuring they are scalable, reliable, secure, and aligned with business requirements.
Work is performed under the supervision of the AI Program Manager.
Duties and Responsibilities
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Defines and owns the product vision, strategy, and roadmap for AI initiatives* .
Translates business needs into technical requirements and user stories* .
Designs, develops, and deploys AI models and applications using modern frameworks* .
Administers and maintains existing AI projects, ensuring operational stability, performance optimization, and timely updates* .
Develops AI Governance and is responsible for AI operations like model monitoring, training, and retraining* .
Coordinates the integration and utilization of data pipelines, APIs, and structured and unstructured data to support enterprise applications and AI initiatives. Integrates AI technologies with core city systems (ERP, GIS, CRM, \& ITSM platforms, etc.* )
Collaborates with cross\-functional teams, engineers, designers, and stakeholders to deliver high\-impact solutions* .
Ensures AI solutions comply with established governance, privacy, security, transparency, and ethical standards* .
Monitors performance, gathers feedback, and iterates on product features* .
Stays current with emerging AI trends, tools, and technologies* .
Performs all other duties and tasks as assigned.
*
Working Conditions
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Mostly office environment.
### All duties and responsibilities listed are subject to change.
MINIMUM QUALIFICATIONS
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### Education
Bachelor's degree### Experience
Three (3\) years of relevant experience### Equivalency
Any combination of relevant education and experience may be substituted on a year\-for\-year basis.
### License/Certifications
Preferred Qualifications
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Education:
Bachelor's Degree
Experience:
Three (3\) years of relevant experience.
Any combination of relevant education and experience may be substituted on a year\-for\-year basis.
Preferred Qualifications:
Experience with generative AI, LLMs, or NLP applications
Proven experience as a Product Owner or Technical Product Manager in AI or data\-driven products
Strong proficiency in Python and AI/ML libraries (e.g., scikit\-learn, PyTorch, TensorFlow)
Experience with cloud platforms (Azure, AWS, or GCP) and MLOps pipelines
Excellent communication and stakeholder management skills
Familiarity with agile methodologies and product lifecycle management
Certifications in AI/ML or product management is a plusPOSITION DETAILS
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### Job Profile
J2025 \- Systems Engineer
View full job profile including classification specifications and physical demands at https://www.tucsonaz.gov/Departments/Human\-Resources/Tucson\-Talent.
### Compensation Grade
G110### Hourly Range
$35\.37 \- 53\.05 USD
The City of Tucson considers several factors when extending an offer, including but not limited to, the role and associated responsibilities, a candidate's work experience, education/training, key skills, and internal equity.
### Fair Labor Standards Act (FLSA)
Exempt### Position Type
Regular### Time Type
Full time### Department
Information Technology### Department Link
No Website### Background Check
This position has been designated to require a criminal background check. The City of Tucson is a Second Chance Employer.
ABOUT US
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### Benefits
The City of Tucson offers a generous benefits package for benefit\-eligible positions. The comprehensive, flexible, and affordable coverage is designed to optimize health and well\-being, security and future, and peace of mind. Benefits begin with medical, dental, vision, life, disability, and FSA coverage, surpassing your standard 401(k) program by offering a rich pension plan plus optional Roth and pretax deferred compensation savings. With your well\-being in mind, our paid time off program provides new hires with 38 paid days off in the first year of employment, with time off increasing steadily in subsequent years. We offer twelve weeks of paid parental leave, paid tuition reimbursement, student loan repayment, off\- and on\-the\-job training, and opportunities to forge connections with peers and the community through employee resource groups and paid volunteer hours. You can learn more about our benefits at https://www.tucsonaz.gov/Departments/Human\-Resources/Employee\-Benefit\-Snapshot.
### Citizenship
The City of Tucson employs only U.S. citizens and lawfully authorized non\-U.S. citizens. All new employees must show employment eligibility verification as required by the U.S. Citizenship and Immigration Services. The City of Tucson does not offer visa sponsorship.
The City of Tucson is an Equal Opportunity/AffirmativeAction/Veterans/Disability Employer
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The city does not discriminate based on race, color, religion, sex (including sexual orientation, gender identity, and pregnancy), national origin, veteran status, age, disability, genetic testing, or any other protected status. If you believe you have been a victim of discrimination, you may file a complaint with the City of Tucson's Office of Equal Opportunity Programs, U.S. Equal Employment Opportunity Commission (EEOC) or Arizona Attorney General's Office of the Civil Rights Division (ACRD).
ADA Accessibility Compliant Form
The City of Tucson is committed to providing access and reasonable accommodation for individuals with disabilities or who require religious accommodation; please contact Human Resources at [email protected].
### Recruiter Name
Liliana Almeraz### Recruiter Email
For general Human Resources questions please contact 520\-837\-4190\.
Salary Context
This $72K-$110K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At City of Tucson, 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 $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($91K) sits 58% below the category median. Disclosed range: $72K to $110K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
City of Tucson AI Hiring
City of Tucson has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Tucson, AZ, US. Compensation range: $110K - $110K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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