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About This Role
The AI Product Software Engineer (Laravel / Vue) is responsible for designing, building, shipping, and continuously improving production software that supports Stanbridge University’s digital ecosystem, including its Learning Management System and related institutional platforms.
This is not a traditional web development role. We are seeking an AI\-first product engineer who uses modern AI tools as a core part of the software development lifecycle to rapidly design, prototype, generate, validate, refine, and deliver production\-ready applications.
Working primarily with Laravel (PHP 8\.x) and Vue.js (Vue 3\), this role transforms business needs and product ideas into intuitive, scalable, secure, and maintainable software.
The ideal candidate combines strong software engineering fundamentals with an AI\-first development mindset and a keen eye for UX/UI. They understand that exceptional software is not measured only by clean code, but also by usability, thoughtful design, accessibility, operational value, and measurable impact.
Success in this role is measured by the quality of the software delivered, the business problems solved, the user experiences created, and the continuous improvement of how software is designed and built.
Essential Duties \& ResponsibilitiesAI Product Engineering* Use AI\-assisted development tools, coding agents, and workflow automation as integral components of daily software engineering.
- Rapidly translate product concepts, operational needs, and user requirements into working prototypes and production\-ready applications.
- Generate, review, validate, and refine AI\-assisted code while maintaining responsibility for architecture, security, quality, performance, and maintainability.
- Use AI throughout implementation, testing, debugging, documentation, refactoring, code review, and technical discovery.
- Develop reusable AI\-assisted workflows, engineering prompts, repository context, templates, and documentation that improve delivery speed and consistency.
- Evaluate emerging AI development tools and identify practical opportunities to improve engineering productivity and software quality.
- Maintain strong technical judgment when determining where AI\-generated solutions require correction, redesign, or manual intervention.
Product Development \& UX/UI* Build software that is intuitive, visually polished, accessible, and aligned with user and institutional needs.
- Apply strong product judgment and a keen eye for UX/UI when designing workflows, interfaces, components, and interactions.
- Translate complex processes into simple, clear, and efficient digital experiences.
- Consider user behavior, accessibility, engagement, conversion, and operational impact when making technical and design decisions.
- Develop and refine user interfaces using Vue.js and modern front\-end development practices.
- Validate that AI\-assisted interfaces meet functional, visual, accessibility, and usability expectations.
- Improve existing applications through thoughtful product iteration, workflow simplification, and user\-centered design.
Software Delivery \& Engineering Execution* Build, ship, test, and maintain production web applications using Laravel, PHP 8\.x, Vue.js, JavaScript, and TypeScript.
- Own assigned features and products from technical discovery through implementation, testing, deployment, monitoring, and continuous improvement.
- Develop reusable Laravel services, REST APIs, Vue components, shared libraries, and internal engineering tools.
- Deliver software in small, reliable increments with a focus on quality, maintainability, accessibility, performance, and security.
- Design and integrate internal and third\-party systems using REST and JSON APIs with resilient error handling.
- Improve existing systems through refactoring, performance optimization, modernization, and architectural enhancements.
- Troubleshoot complex application issues across the full stack.
- Participate in code reviews that improve readability, consistency, reliability, and engineering quality.
- Contribute to technical documentation, system design decisions, and engineering standards.
Quality, Reliability \& Security* Write clean, maintainable, secure, and production\-ready software.
- Develop automated tests using PHPUnit, Pest, Playwright, Cypress, or equivalent frameworks.
- Participate in GitHub\-based development workflows, pull requests, automated testing, and CI/CD pipelines.
- Review AI\-generated code for security vulnerabilities, architectural inconsistencies, performance issues, and maintainability risks.
- Apply secure coding practices aligned with OWASP recommendations.
- Implement appropriate input validation, authorization, authentication, dependency management, and secure handling of sensitive information.
- Follow university data\-handling policies and FERPA requirements when developing software and using AI\-assisted engineering tools.
- Contribute to logging, monitoring, observability, incident response, and preventative reliability improvements.
- Build responsive and accessible interfaces aligned with WCAG 2\.2 AA standards.
Innovation \& Continuous Improvement* Identify opportunities to simplify, automate, and improve institutional workflows through software.
- Improve engineering velocity through reusable code, automation, documentation, AI\-assisted workflows, and standardized development practices.
- Create shared engineering assets that reduce repetitive work and accelerate future development.
- Contribute ideas that improve developer productivity, product quality, user experience, and operational efficiency.
- Stay current with emerging AI tools, development practices, software frameworks, and product\-engineering methods.
- Share knowledge through collaboration, documentation, code review, and technical mentoring.
- Help foster an engineering culture centered on innovation, craftsmanship, accountability, curiosity, and reliable delivery.
QualificationsRequired Qualifications
- Five or more years of professional experience building and shipping production web applications in a SaaS, enterprise, or similarly complex environment.
- Strong hands\-on experience developing production applications with Laravel and PHP 8\.x.
- Strong experience with Vue.js, preferably Vue 3, and modern JavaScript or TypeScript development.
- Demonstrated use of AI\-assisted development tools as an integral part of the daily software engineering workflow.
- Ability to critically review, validate, debug, and improve AI\-generated software.
- Strong software engineering fundamentals, including application architecture, testing, debugging, data modeling, security, and maintainability.
- Experience designing, developing, and integrating RESTful APIs.
- Strong understanding of relational databases, including MySQL or MariaDB, schema design, migrations, indexing, and query optimization.
- Experience writing automated tests using PHPUnit, Pest, Playwright, Cypress, or equivalent frameworks.
- Experience with Git, GitHub workflows, pull requests, and modern CI/CD pipelines.
- Ability to work across the full application stack and understand the software produced through AI\-assisted development.
- Strong product judgment and a demonstrated ability to translate user or business needs into practical software solutions.
- Keen eye for UX/UI, usability, accessibility, and visual quality.
- Strong debugging, troubleshooting, analytical, and problem\-solving skills.
- Strong written and verbal communication skills.
- Ability to take ownership of work from concept through production.
Preferred Qualifications
- Experience using tools such as Claude Code, Cursor, GitHub Copilot, ChatGPT, OpenAI APIs, or comparable AI development platforms.
- Experience building AI\-powered features, integrating LLM APIs, or developing agent\-based workflows.
- Experience developing or supporting Learning Management Systems, Student Information Systems, educational technology platforms, or enterprise applications supporting higher education.
- Experience working in education, healthcare, or another regulated environment.
- Experience designing internal business applications or workflow\-automation platforms.
- Experience with product discovery, prototyping, user research, marketing technology, conversion optimization, or digital experience design.
- Experience building reusable component libraries, shared services, engineering templates, or internal developer tooling.
- Experience with Docker, Redis, AWS, Vite, GitHub Actions, or modern Laravel development tooling.
- Familiarity with design systems, responsive design, accessibility standards, and modern UX/UI principles.
- Familiarity with OWASP secure coding practices and WCAG 2\.2 AA accessibility standards.
- Experience improving engineering productivity through automation, reusable patterns, AI agents, or workflow optimization.
Knowledge, Skills \& Abilities* Strong Laravel, PHP, Vue.js, JavaScript, and full\-stack web application development skills.
- Advanced ability to use AI\-assisted engineering tools effectively and responsibly.
- Ability to evaluate AI\-generated code for correctness, security, maintainability, and architectural fit.
- Strong product\-thinking and user\-centered problem\-solving abilities.
- Keen visual judgment and sensitivity to UX/UI quality.
- Ability to transform ambiguous ideas into functional, polished software.
- Strong understanding of application architecture, APIs, databases, testing, security, and production operations.
- Ability to balance rapid delivery with software quality and long\-term maintainability.
- Strong ownership, accountability, and independent execution.
- Ability to communicate technical concepts clearly to technical and non\-technical stakeholders.
- Ability to manage multiple priorities in a fast\-paced, iterative environment.
- Curiosity, adaptability, and commitment to continuous learning.
Compensation
Competitive compensation package based on education, professional experience, technical expertise, and internal equity considerations.
Conditions of Employment* A job\-related assessment may be required during the interview process.
- Must be able to perform each essential duty satisfactorily and be physically present in the office unless otherwise noted.
- Employment verification will be conducted to validate work experience in accordance with accreditation standards.
- Offers of employment are contingent upon successful completion of a background check.
- Official transcripts are required before hire.
- Degrees earned outside the United States must be evaluated by a recognized credential\-evaluation service to determine U.S. degree equivalency and applicable subject\-area coursework.
- Must be legally authorized to work in the United States at the time of hire and maintain work authorization throughout employment.
- Stanbridge University does not provide employment visa sponsorship for this position.
- Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the position.
Work Environment* Standard office, classroom, laboratory, clinical, or remote work environment depending on operational requirements.
- Duties are primarily performed while working at a computer workstation.
- Work may occasionally occur within laboratory or clinical\-simulation environments supporting academic programs.
- Work is performed in a collaborative environment with competing priorities, product deadlines, and occasional interruptions.
Physical Demands* Regularly sits for extended periods while working at a computer.
- Frequently uses computers, keyboards, monitors, and standard office equipment.
- Communicates effectively in person, by telephone, and through video conferencing.
- Reads detailed technical documentation and computer displays.
- Occasionally lifts, carries, or moves objects weighing up to 25 pounds.
Employee Benefits* Health Care Plan: Medical, Dental, and Vision
- Retirement Plan: 401(k)
- Paid Time Off: Vacation, Sick Leave, and Public Holidays
- Family Leave: Maternity and Paternity
- Life Insurance: Basic, Voluntary, and AD\&D
- Work/Life Balance initiatives
- Employee wellness program
- On\-campus wellness services
- University events and professional\-development opportunities
Institutional ValuesDiversity \& Inclusion
Stanbridge University’s motto, “Strength through Diversity,” reflects our commitment to fostering an inclusive learning environment that values the diverse backgrounds, perspectives, and experiences of our students, faculty, staff, and surrounding communities.
Innovation \& Technology
We embrace thoughtful innovation and modern technology to improve learning, operations, and the student experience while preparing graduates for the demands of today’s healthcare professions.
Community Engagement
Through initiatives such as Stanbridge outREACH, students are empowered to serve local and global communities while developing compassion, civic responsibility, and professional excellence.
Equal Opportunity Employer
Stanbridge University is an Equal Opportunity Employer committed to building a diverse and inclusive workplace. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, sexual orientation, gender identity, veteran status, or any other protected status under applicable law. All qualified applicants are encouraged to apply.
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Stanbridge University, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $218,500 based on 729 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Stanbridge University AI Hiring
Stanbridge University has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Irvine, CA, US.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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.
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