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About This Role
About Us
SCG America Group Inc. is a New York City-based company with operations in construction, property management, and food & beverage. We are looking for a hands-on Software Engineer Intern to help us build a practical, AI-assisted internal tool for day-to-day property and administrative management.
About the Project
Our property management work currently lives across Microsoft To Do, Excel, Word, PDFs, and email. Tasks, contracts, tenant insurance, leases, and payment records are scattered, sync between phone and desktop is unreliable, and key dates depend on manual tracking. This project will replace that patchwork with a single web-based system that combines simple to-do reminders, spreadsheet-style structured data, document management, and built-in AI assistance. You will work directly with the end user, turning real daily pain points into working features.
What You Will Build
- Tasks & Reminders: create tasks with due dates, recurring reminders, priority, status (Not Started / In Progress / Done), and categories (Property, Contract, Insurance, Payment, Tenant, Vendor, Other), with fast search and filtering.
- Structured Records: spreadsheet-style tables for properties, contacts, contract dates, insurance expirations, amounts, status, notes, attached files, and next actions; sorting, filtering, and Excel import/export.
- Property & Tenant Tracking: lease expirations, renewal notices, rent escalations, tenant insurance, maintenance follow-ups, and document receipt; views such as "tenant items due in the next 30 days" or "lease renewals in the next 90 days."
- Vendor / Subcontractor Directory: a searchable contact directory linked to related records.
- Contracts & Key Dates: track effective, expiration, renewal, and notice deadlines, payment milestones, and insurance requirements, linked to the source documents.
- Payments, Invoices & Recurring Items: track vendor/subcontractor invoices, payment applications, pending approvals, missing documents, recurring payments, and payroll/timesheet checks to prevent missed or duplicate payments.
- Unified Workspace: each item brings together its tasks, deadlines, contacts, structured data, contracts/PDFs, invoices, email records, history, and AI analysis in one place.
- Built-in AI Features (using free, open-source models that run locally): summarize contracts, insurance certificates, leases, and other PDFs; extract dates, company names, amounts, and expiration terms from documents; natural-language search across stored records and files; answer questions from documents with source citations for human verification; analyze spreadsheet data and generate management summaries and follow-up suggestions.
- Cross-Device Access: browser-based on desktop with a mobile-friendly interface, one shared data source, and backup/export capabilities.
Technical Constraints
- $0 initial cost: open-source frameworks, a free local database, free local development tools, open-source local AI models, and free document-processing/search components.
- Must install and run on an existing laptop; may integrate with existing OneDrive / Microsoft 365 storage where applicable.
Qualifications
- Currently pursuing or recently completed a degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related field
- Experience building web applications (front end and back end) through coursework, projects, or prior internships
- Working knowledge of at least one modern stack (e.g., Python, JavaScript/TypeScript) and relational databases (e.g., SQLite, PostgreSQL)
- Interest in applied AI: local LLMs, document parsing, or retrieval-augmented search
- Able to work independently, communicate clearly in English, and translate non-technical requirements into working features
Nice to Have
- Experience with open-source local LLM tools (e.g., Ollama, llama.cpp) and PDF/OCR processing
- Familiarity with Excel data import/export and responsive (mobile-friendly) web design
- A portfolio or GitHub profile showing completed projects
Internship Details
- Location: Remote (must reside in the United States)
- Schedule: Part-time, 20-30 hours per week
- Duration: 3 months; may be extended depending on project progress
- An internship completion letter will be provided upon successful completion.
- Work Authorization: Must be authorized to work in the U.S.; F-1 students eligible for CPT or OPT are welcome to apply. Visa sponsorship is not available.
How to Apply
Please apply through Indeed with your resume. A link to your GitHub or portfolio is strongly encouraged.
Expected hours: No more than 30.0 per week
Work Location: Remote
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 9,653 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At SCG America Group Inc., 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 $220,000 based on 1,448 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $110,408.
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.
SCG America Group Inc. AI Hiring
SCG America Group Inc. has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Remote, US.
Remote Work Context
Remote AI roles pay a median of $185,906 across 2,124 positions. About 6% of all AI roles offer remote work.
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 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).
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 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.
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