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About This Role
POSITION OVERVIEW
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Applications accepted from: ALL PERSONS INTERESTEDDivision: OFFICE OF THE CIOReporting Location: 611 WALKER / 1200 TRAVISWorkdays \& Hours: MONDAY – FRIDAY, Office Hours DESCRIPTION OF DUTIES / ESSENTIAL FUNCTIONS
Houston, TX, is the fourth largest city in the country, with a budget of over 6 billion dollars, a workforce strong of 20,000 employees, and 23 departments with fascinating data and a wide range of questions. Houston promotes healthy and resilient communities through smart civic investments, dynamic partnerships, education, and innovation. It is a place where anyone can prosper and feel at home.
The City offers its employees various benefits, including healthcare, wellness, professional development, and an excellent pension plan (Download PDF reader).
The IT Architect – Applications (Responsible AI and Innovation) serves as the City’s enterprise leader for artificial intelligence strategy, governance, and adoption. Reporting to the Office of the CIO – Performance, Architecture, and Innovation, this role advances responsible AI capabilities that improve operational efficiency, support data\-driven decision\-making, and enhance public services across all City departments. The position blends strategic architecture, innovation leadership, and hands\-on solution engagement, ensuring that AI initiatives are secure, ethical, scalable, and aligned with enterprise architecture standards.
KEY RESPONSIBILITIES* Governance
+ Lead the development and continuous refinement of the City’s enterprise\-wide AI strategy, aligned with City’s priorities and departmental needs.
+ Establish and maintain AI governance frameworks, ensuring transparency, accountability, data privacy, and regulatory compliance.
+ Integrate AI oversight into existing governance bodies and support decision\-making related to intake, review, and approval of AI initiatives.
- Use Case Development
+ Identify, evaluate, and prioritize impactful AI use cases; support departments in framing business challenges and translating them into AI opportunities.
+ Conduct exploratory pilots and proofs\-of\-concept, including participation in procurement activities such as RFP development, vendor evaluations, and SOW reviews.
+ Actively engage in hands\-on experimentation with AI tools, models, and platforms to validate feasibility and guide architectural recommendations.
- Stakeholder Engagement
+ Foster partnerships across City departments, providing clear communication on AI opportunities, risks, and value.
+ Collaborate with all divisions across HITS and Federated IT to ensure convergence on AI initiatives.
+ Support Digital Champions in departments through coaching, knowledge\-sharing, and hands\-on enablement to accelerate AI literacy and adoption.
- Capability Building
+ Serve as a technical advisor and architect on AI\-related initiatives, ensuring alignment with enterprise architecture, data platforms, and security standards.
+ Review technical designs, data\-integration patterns, and project documentation; identify risks and recommend mitigation strategies to delivery teams.
+ Monitor AI industry trends, standards, and regulatory developments to keep the City’s practices current and compliant.
- Other duties as assigned.
QUALIFICATIONS* Hands\-on experience with modern AI and data platforms, including Azure AI, Microsoft Copilot, machine\-learning frameworks, and API\-based AI services.
- Strong understanding of data governance, security, privacy, and responsible\-AI principles within regulated or public\-sector environments.
- Demonstrated ability to translate business needs into viable AI opportunities, including assessing feasibility, risk, and expected impact.
- Extensive experience in enterprise IT architecture, particularly in the design or governance of AI, data, or analytics solutions.
- Proven ability to review or develop technical architectures, solution designs, reference architectures, and technical standards.
- Ability to lead pilots and proofs\-of\-concept and guide them toward scalable enterprise deployment.
- Experience supporting digital champions, communities of practice, or capability\-building programs that promote adoption of emerging technologies.
- Strong communication and stakeholder\-engagement skills, with the ability to collaborate across divisions, departments, and federated IT groups.
- Familiarity with IT governance processes, including RFP/SOW development, vendor evaluations, and project\-risk assessment.
Compliance \& Security Requirements:* CJIS Certification (or ability to obtain within 90 days of hire) is mandatory.
- Must successfully pass a comprehensive background check, including criminal history, and fingerprinting per Houston Police Department and CJIS standards.
- Candidate must maintain eligibility for access to sensitive law enforcement systems and data.
WORKING CONDITIONS
There are no major sources of discomfort, i.e., essentially normal office environment with acceptable lighting, temperature, and air conditions. Significant time spent using computer display, keyboard, and mouse.
MINIMUM REQUIREMENTS
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EDUCATION
Requires a Bachelor's degree in Computer Science, Management and Information Systems (MIS) or a closely related field.
Holds multiple applications\-specific technical certifications; recognized as having mastery of a particular technical discipline.
A Master's degree in Computer Science, Management and Information Systems (MIS) or a closely related field may be substituted for up to two (2\) years of experience.
EXPERIENCE
At least ten (10\) years of specialized experience in application systems analysis and development.
LICENSE
None
PREFERENCES
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*\*\*Preference shall be given to eligible veteran applicants provided such persons possess the qualifications necessary for competent discharge of the duties involved in the position applied for, such persons are among the most qualified candidates for the position, and all other factors in accordance with Executive Order 1\-6\. \*\**
*Preference will be given to candidates with the following skillsets:** Demonstrated leadership in shaping or influencing organizational AI strategy, such as contributing to an AI council, innovation board, technology steering committee, or enterprise governance forum.
- Experience launching or scaling citywide or enterprise\-wide innovation programs, including hackathons, AI communities of practice, capability\-building cohorts, or digital\-champion networks.
- Established partnerships with academic institutions, civic\-tech organizations, or industry research groups to advance responsible AI innovation in the public sector.
- A track record of guiding organizations through emerging\-technology change, including developing ethical\-AI guidelines, contributing to policy development, or supporting adoption across federated IT environments.
- Knowledge of SDLC, ITIL, and Agile/DevOps methodologies supporting modern solution delivery.
- Relevant industry certifications in AI, cloud, or data technologies.
- Zachman (ZCEA) or TOGAF certification
GENERAL INFORMATION
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SELECTION / SKILLS TESTS REQUIRED
Department may administer skills assessment test
SAFETY IMPACT POSITION– NO
If *yes*, this position is subject to random drug testing and if a promotional position, candidate must pass an assignment drug test.
SALARY INFORMATION Factors used in determining the salary offered include the candidate’s qualifications as well as the pay rates of other employees in this classification.
*PAY GRADE*: 33
APPLICATION PROCEDURES
*Only online applications will be accepted* for this City of Houston job and must be received by the Human Resources Department during active posting period. Applications must be submitted online at: www.houstontx.gov.
To view your detailed application status, please log\-in to your online profile by visiting:http://agency.governmentjobs.com/houston/default.cfmor call (832) 393\-0450.
If you need special services or accommodations, call (832\) 393\-0450\. (7\-1\-1\).
If you need login assistance or technical support call 855\-524\-5627.
Due to the high volume of applications received, the Hiring Department will contact you directly, should you be selected to advance in our recruitment process.
All new and rehires must pass a pre\-employment drug test and are subject to a physical examination and verification of information provided.
*EOE Equal Opportunity Employer*
The City of Houston is committed to recruiting and retaining a diverse workforce and providing a work environment that is free from discrimination and harassment based upon any legally protected status or protected characteristic, including but not limited to an individual's sex, race, color, ethnicity, national origin, age, religion, disability, sexual orientation, genetic information, veteran status, gender identity, or pregnancy.
Employer
City of Houston
Address
901 Bagby St
Houston, Texas, 77002
Website
https://www.houstontx.gov/
Salary Context
This $110K-$135K range is in the lower quartile for AI Safety roles in our dataset (median: $222K across 8 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 2,799 AI roles we're tracking, AI Safety positions make up 0% of the market. At City of Houston, TX, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Safety roles pay a median of $274,200 based on 43 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $159,385. This role's midpoint ($122K) sits 55% below the category median. Disclosed range: $110K to $135K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $252,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and Research Engineer ($260,000). By seniority level: Entry: $97,760; Mid: $159,385; Senior: $227,500; Director: $242,000; VP: $250,000.
City of Houston, TX AI Hiring
City of Houston, TX has 1 open AI role right now. They're hiring across AI Safety. Based in Houston, TX, US. Compensation range: $135K - $135K.
Location Context
Across all AI roles, 16% (460 positions) offer remote work, while 2,318 require on-site attendance. Top AI hiring metros: New York (2,241 roles, $208,300 median); San Francisco (1,822 roles, $252,000 median); Los Angeles (1,611 roles, $188,900 median).
Career Path
Common paths into AI Safety roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 2,799 open positions tracked in our dataset. By seniority: 98 entry-level, 1,283 mid-level, 1,092 senior, and 326 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (460 positions). The remaining 2,318 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $252,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 30 roles); AI Safety ($274,200 median, 43 roles); Research Engineer ($260,000 median, 387 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 2,799 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (1,978), AI Software Engineer (197), Data Scientist (195). 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 (98) are outnumbered by mid-level (1,283) and senior (1,092) 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 326 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (460 positions), with 2,318 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 $200,000. Top-quartile roles start at $252,000, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,433 postings), Aws (840 postings), Rag (663 postings), Azure (639 postings), Gcp (537 postings), Pytorch (445 postings), Prompt Engineering (418 postings), Claude (396 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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