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About This Role
Associate AI Engineer
Kickstart your career in AI! We're looking for Associate AI Engineers to join our Central AI team. This role is perfect for someone smart and innovative who is eager to apply what they've learned in school (or internships) and grow into an AI\-focused career path. Working in our Newark office, you'll collaborate with various departments and teams to develop and deploy next\-generation AI tools that power smarter business decisions \- learning hands\-on, while making an impact from day one.
This is a unique chance to convert your passion for AI and automation into real\-world solutions that drive organization\-wide transformation across Internet Brands.
What You’ll Do:
- Assist in Design and Documentation – Support senior team members by understanding business and product requirements, helping to determine possible solutions, documenting designs or simple solutions, and clearly communicating updates and technical details within the team.
- Development of AI Enhanced Products – Develop internal and client facing solutions, leveraging Agentic AI to produce highly automated systems that may perform complex workflows through AI reasoning, acting, observing, planning, and self\-refining.
- Supporting \& Operationalization \- Learn to deploy and validate your code in integration and production environments using standard build and merge processes. Gain exposure to key DevOps tools within our infrastructure, including basic logging, monitoring, and release workflows.
- Development Support – Assist in troubleshooting, investigating issues, and applying fixes to ensure smooth operation of applications and services.
About You:
- Bachelors degree in Computer Science, Data Science, Applied Mathematics, (or any other engineering discipline)
- Strong programming skills with an object\-oriented approach and understanding of security best practices. Experience with at least one modern programming language and its ecosystem.
- Generative AI, Prompt Engineering \& Agentic AI \- Practical experience working with generative AI models such as GPT, Claude, and similar LLMs. Experience with coding agents, such as Claude Code, Cursor, Windsurf, and Gemini CLI.
- Adaptability \& Learning Mindset \- Willingness and ability to quickly learn and adapt to new technologies, frameworks, and tools as needed. Open to working across the stack to support the development of AI\-powered solutions. Comfortable stepping beyond core skill sets to contribute wherever needed in the AI application lifecycle.
- Communication Skills \- Strong verbal and written communication skills to effectively collaborate with team members, understand business requirements, and clearly document solutions and updates.
Bonus Points:
- Version control system \- Experience with version control systems like Git, including basic workflows such as branching and merge requests.
- Unit Testing \- Experience writing and running automated tests with any testing framework to ensure code quality and reliability. Able to catch bugs early through strong unit testing habits.
- Able to craft prompts to drive contextually relevant outputs and build basic agentic workflows (e.g., tool usage, multi\-step reasoning, or dynamic context handling). Experience integrating LLM APIs to build AI\-powered features and workflows.
Why You'll Love This Role:
- Work on projects that matter. See results or learn from failures quickly.
- Exposure to developing automated AI solutions in business. Direct influence on AI implementation projects with real business impact.
- Hands\-on learning and mentorship. Opportunities to evolve and explore different areas of GenAI and Technology. .
- A collaborative, supportive team environment.
At Internet Brands, we carefully consider a wide range of factors when determining compensation, including your background and experience. These considerations can cause your compensation to vary. We expect the compensation for this role to start at $60k and will depend on your skills, qualifications, and experience. We encourage all interested candidates to apply.
In addition to our awesome culture, we offer a comprehensive benefits package designed to support the health and well\-being of you and your family. Our benefits include health insurance options such as medical, dental, and vision coverage, flexible spending accounts (FSA) for medical and dependent care, short\-term and long\-term disability insurance, and life and AD\&D insurance. We also provide a 401(k) retirement savings plan with a company match, paid time off (PTO), paid holidays, as well as access to our Employee Assistance Program (EAP) and well\-being coaching services. In addition, employees can take advantage of voluntary benefits such as home, auto and pet insurance, and discounted legal and financial services. For more details, feel free to inquire during the interview process.
Internet Brands®, headquartered in El Segundo, Calif, is a fully integrated online media and software services company focused on four high\-value vertical categories: Health, Automotive, Legal, and Home/Travel. The company's properties and platforms include the WebMD, Medscape, and Henry Schein ONE networks, which are the global leaders in their markets; Nolo, Avvo, and Martindale, which form the largest consumer information provider in the legal market; and CarsDirect, Fodor's Travel, and many others which are leaders in their key vertical markets. Internet Brands' award\-winning consumer websites lead their categories and serve more than 250 million monthly visitors, while a full range of web presence offerings has established deep, long\-term relationships with SMB and enterprise clients. The company's powerful, proprietary operating platform provides the flexibility and scalability to fuel the company's continued growth. Internet Brands is a portfolio company of KKR and Warburg Pincus.
Internet Brands is an equal opportunity employer, and we welcome applicants from all backgrounds. We comply with all applicable laws and regulations, including the City of Los Angeles Fair Chance Initiative for Hiring Ordinance (FCIHO).
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 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Internet Brands, 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 $219,250 based on 424 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $120,000.
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.
Internet Brands AI Hiring
Internet Brands has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Newark, NJ, US.
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 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 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).
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 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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