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Position Information
Working Title of Vacant Position Enterprise AI \& Analytics Program Manager
Job Type Full Time
Posting Type Public
Number of Vacancies 1
Department INFORMATION TECHNOLOGY
Division IT ADMINISTRATION
Requisition Number 2026330
Number of hours worked per week 40
Work Schedule
Monday – Friday 8:00am – 5:00pm
*Employees may be expected to work hours in excess of their normally scheduled hours in response to short\-term department needs and/or City\-wide emergencies.*
Work Site Location Chesapeake, VA
Position Driving Requirement O \- Occasional
Pay Grade GE22
Pay Basis Semi\-Monthly
Advertised Salary
Starting Range: $96,104\-$142,955
- Starting salary commensurate with education and experience.
Job Description
The City of Chesapeake is seeking an innovative and strategic Enterprise AI \& Analytics Program Manager to lead the development and implementation of enterprise artificial intelligence (AI), advanced analytics, and digital transformation initiatives.
Reporting directly to the Chief Information Officer, this newly created leadership position will help shape how the City leverages AI and data to improve government operations, enhance customer service, strengthen decision\-making, and deliver measurable value to residents, businesses, visitors, and City employees.
If you are passionate about applying emerging technologies to solve complex business challenges and want to make a meaningful impact in public service, we encourage you to apply.
Key responsibilities include:* Develop and manage the City’s Enterprise AI \& Analytics Program and strategic roadmap.
- Partner with City leadership to identify opportunities where AI and analytics can improve services and operations.
- Lead enterprise AI governance, responsible AI practices, and technology standards.
- Manage a portfolio of AI, analytics, and digital transformation initiatives.
- Design and implement predictive analytics, dashboards, and performance measurement solutions.
- Evaluate emerging technologies and recommend innovative business solutions.
- Support data\-informed decision\-making through advanced analytics and business intelligence.
- Promote AI literacy and organizational adoption through collaboration, education, and change management.
- Ensure AI initiatives align with cybersecurity, privacy, regulatory, and ethical standards.
- Partner with departments to identify operational challenges and opportunities for innovation.
- Conduct business process assessments and identify opportunities for automation, optimization, and modernization.
- Develop educational resources, training programs, and workshops for City employees and leadership
What We’re looking for:
The ideal candidate is a strategic thinker with strong business acumen who can bridge technology and organizational priorities. You should have experience leading enterprise initiatives, managing cross\-functional projects, and communicating complex technical concepts to executive and non\-technical audiences.
Successful candidates will possess:* Experience in artificial intelligence, advanced analytics, business intelligence, digital transformation, or enterprise technology programs.
- Knowledge of AI governance, machine learning, generative AI, predictive analytics, and data visualization.
- Experience developing business cases, strategic plans, and executive\-level presentations.
- Strong collaboration, project management, and problem\-solving skills.
- A passion for innovation and continuous improvement.
The City of Chesapeake offers an exceptional range of benefits.
Required Qualifications
Vocational/Educational Requirement: Requires any combination of education and experience equivalent to a bachelor’s degree in computer science, computer information systems, information technology, or a related field. Master’s degree preferred.
Experience: In addition to satisfying the vocational/education standards, this class requires a minimum of seven years of related, full\-time equivalent experience.
Special Certifications and License: Requires a valid driver’s license and a driving record that is in compliance with City Driving Standards. A technical, IT customer service, or project management associated certification is preferred.
Special Requirement(s): Employees may be expected to work hours in excess of their normally scheduled hours in response to short\-term department needs and/or City\-wide emergencies. Emergency operations support work and work locations may be outside of normal job duties.
Preferred Qualifications
Experience presenting recommendations and findings to executive leadership.
Professional certifications in AI, analytics, cloud technologies, or project management.
Experience leading cross\-functional technology or business initiatives.
Posting Detail Information
Job Open Date 07/08/2026
Job Close Date 07/22/2026
Open Continuous No
Special Instructions to Applicants
This position is not eligible for third\-party (i.e., contractor/staffing agency) placements. For questions about this position, please email selection@cityofchesapeake.net.
ADA Checklist
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Overall Physical Strength Demands
Overall Physical Strength Demands S\=Sedentary \- Exerting up to 10 lbs. occasionally or small weights frequently; sitting most of the time.
Physical Demands
C \= Continuously\- 2/3 or more of the time. F \= Frequently\- From 1/3 to 2/3 of the time. O \= Occasionally\- Up to 1/3 of the time. R \= Rarely\- Less than 1 hour per week. N \= Never\- Never occurs.
Standing Rarely\- Less than 1 hour per week.
Sitting Continuously\- 2/3 or more of the time.
Walking Rarely\- Less than 1 hour per week.
Lifting N \= Never
Lifting Amount N/A
Carrying Rarely\- Less than 1 hour per week.
Carrying Weight Exerting up to 10 lbs
Pushing/Pulling N \= Never
Pushing/Pulling Weight N/A
Reaching No Response
Handling No Response
Fine Dexterity Continuously\- 2/3 or more of the time.
Kneeling N \= Never
Crouching Never\- Never occurs.
Crawling Never\- Never occurs.
Bending Never\- Never occurs.
Twisting N \= Never
Climbing Never\- Never occurs.
Balancing Never\- Never occurs.
Vision Continuously\- 2/3 or more of the time.
Hearing Continuously\- 2/3 or more of the time.
Talking Frequently\- From 1/3 to 2/3 of the time.
Foot Controls N \= Never
Machines, Tools, Equipment and Work Aids Used
Protective Equipment Required
Health and Safety
D \= Daily W \= Several Times Per Week M \= Several Times Per Month S \= Seasonally N \= Never
Mechanical Hazards N \= Never
Chemical Hazards N \= Never
Electrical Hazards N \= Never
Fire Hazards N \= Never
Explosives N \= Never
Communicable Diseases N \= Never
Physical Danger or Abuse N \= Never
Other
If Other, Description
Environmental Factors
D \= Daily W \= Several Times Per Week M \= Several Times Per Month S \= Seasonally N \= Never
Dirt and Dust N \= Never
Extreme Temperatures N \= Never
Noise and Vibration N \= Never
Fumes and Odors N \= Never
Wetness/Humidity N \= Never
Darkness or Poor Lighting N \= Never
Primary Work Location Office Environment
Non\-Physical Demands
C \= Continuously\- 2/3 or more of the time. F \= Frequently\- From 1/3 to 2/3 of the time. O \= Occasionally\- Up to 1/3 of the time. R \= Rarely\- Less than 1 hour per week. N \= Never\- Never occurs.
Time Pressures Occasionally\- Up to 1/3 of the time.
Emergency Situations Rarely\- Less than 1 hour per week.
Frequent Change of Tasks Occasionally\- Up to 1/3 of the time.
Irregular Work Schedule/Overtime Occasionally\- Up to 1/3 of the time.
Performing Multiple Tasks Simultaneously Continuously\- 2/3 or more of the time.
Working Closely with Others as Part of a Team Continuously\- 2/3 or more of the time.
Tedious or Exacting Work Frequently\- From 1/3 to 2/3 of the time.
Noisy/Distracting Environment Rarely\- Less than 1 hour per week.
Other
If Other, Description
Can anyone assist the employee in performing the primary tasks assigned to this position? If yes, identify the eligible task(s)
Position will be the subject matter expert.
Professional References
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Professional References
Please provide contact information for professional references.
Minimum Requests 0
Maximum Requests 4
Salary Context
This $96K-$142K 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 Chesapeake, 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 in Demand for This Role
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 ($119K) sits 45% below the category median. Disclosed range: $96K to $142K.
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 Chesapeake AI Hiring
City of Chesapeake has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Chesapeake, VA, US. Compensation range: $142K - $142K.
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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