MAANG is an acronym for five of the most influential technology companies in the world: Meta, Apple, Amazon, Netflix, and Google (Alphabet). The term is widely used in tech career circles as shorthand for elite employers known for high compensation, rigorous hiring standards, and industry-shaping products. If you’ve seen the term on a job board, a coding prep site, or a LinkedIn post, it’s referring to this specific group of companies and the culture of competitive hiring that surrounds them.
The Companies Behind the Acronym
Each letter in MAANG represents one company:
- M — Meta Platforms (formerly Facebook), which operates Facebook, Instagram, WhatsApp, and its metaverse division
- A — Apple, the hardware and software giant behind the iPhone, Mac, and iOS ecosystem
- A — Amazon, spanning e-commerce, cloud computing (AWS), streaming, and logistics
- N — Netflix, the streaming service that pioneered subscription-based entertainment
- G — Google (Alphabet), which dominates search, online advertising, Android, YouTube, and cloud services
These five companies aren’t grouped together because of a formal business alliance. They’re grouped because they share a reputation for hiring top engineering talent, paying premium salaries, and setting the bar for technical interviews across the industry. Landing a role at any of them carries significant weight on a resume.
How FAANG Became MAANG
The original acronym was FANG, coined by CNBC’s Jim Cramer in 2013 to describe four high-performing tech stocks: Facebook, Amazon, Netflix, and Google. Apple was added shortly after, turning it into FAANG. The acronym stuck for years, becoming a fixture in both investing and career conversations.
In October 2021, Facebook rebranded itself as Meta Platforms to reflect its focus on virtual and augmented reality. That corporate name change turned FAANG into MAANG in casual usage. Some people also rearranged the letters to spell MANGA. The underlying group of companies stayed the same; only the label shifted.
Why MAANG Matters for Tech Careers
For software engineers, data scientists, product managers, and other tech professionals, MAANG companies represent a specific tier of employer. Starting salaries for software engineers at these firms often exceed $150,000, and total compensation packages that include stock grants and bonuses can push well beyond $200,000 for mid-level roles. Senior engineers and managers can earn significantly more.
Beyond pay, a stint at a MAANG company signals to future employers that you passed a famously selective hiring process and worked at scale. These companies serve hundreds of millions or billions of users, which means their engineering challenges involve distributed systems, massive data pipelines, and infrastructure problems that most companies never encounter. That experience opens doors for the rest of your career, whether you stay in big tech or move to a startup.
The MAANG Interview Process
MAANG companies are known for multi-stage interviews that test both technical skill and problem-solving ability. While each company has its own variations, the general pattern for a software engineering role follows a predictable structure.
The process typically starts with a recruiter screen, where someone from the hiring team reviews your background and confirms basic qualifications. If you pass, you’ll move to an online assessment or technical phone screen. This usually involves solving one or two coding problems in real time, often focused on data structures and algorithms (commonly abbreviated DSA). You’ll write code in a shared editor while explaining your thought process.
Candidates who perform well advance to a virtual or on-site interview loop, which consists of four to six back-to-back interviews over several hours. These rounds cover algorithmic coding, system design (where you sketch out the architecture for a large-scale application), and behavioral questions about teamwork, conflict resolution, and leadership. Some companies add a round focused on domain-specific knowledge or a “bar raiser” interview designed to assess whether you meet the company’s overall hiring standard.
Preparation for this process is an industry in itself. Platforms like LeetCode, HackerRank, and AlgoExpert exist largely because of demand from candidates targeting these companies. Many candidates spend weeks or months practicing hundreds of coding problems before applying.
Related Acronyms You’ll See
MAANG isn’t the only acronym floating around. As the tech landscape has evolved, so have the groupings people use.
MAMAA (Meta, Apple, Microsoft, Amazon, Alphabet) swaps out Netflix for Microsoft, reflecting Microsoft’s dominance in cloud computing, enterprise software, and its massive investment in AI through its partnership with OpenAI. This grouping focuses more on market capitalization and business influence than on hiring culture.
The Magnificent Seven is an investing term for seven stocks that drove a disproportionate share of market returns in recent years: Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla. This is a Wall Street label, not a career label, but you’ll see it in financial news alongside MAANG references.
FAANG+ was an informal expansion that added companies like Microsoft and Tesla to the original five. It never had a fixed definition, which is partly why it faded in favor of more specific groupings.
MAANG in an AI-Driven Market
The hiring landscape at these companies has shifted in recent years. After aggressive hiring during the pandemic, most MAANG companies went through significant rounds of layoffs in 2022 and 2023, cutting tens of thousands of roles. Hiring has since recovered in targeted areas, but the emphasis has moved sharply toward artificial intelligence and machine learning.
Roles involving large language models, generative AI infrastructure, and AI-powered product features now dominate job listings at these firms. Traditional software engineering roles still exist, but candidates with AI and ML experience have a clear advantage. This mirrors a broader industry trend: executive adoption of AI tools is expected to double within the next few years, and companies across sectors are restructuring teams around AI capabilities.
For job seekers, this means that “preparing for MAANG” in 2025 looks different than it did even two years ago. Algorithmic coding skills remain essential, but familiarity with machine learning concepts, cloud-based AI services, and system design for AI workloads increasingly separates competitive candidates from the pack.
Is Targeting MAANG Worth It?
Working at a MAANG company isn’t the only path to a successful tech career, and it’s not the right fit for everyone. The interview process is time-intensive, rejection rates are high, and the work culture at large tech companies can feel bureaucratic compared to smaller firms. Some engineers prefer startups for their faster pace, broader responsibilities, and equity upside.
That said, the compensation, brand recognition, and engineering resources at these companies are hard to match elsewhere. If you’re early in your career and willing to invest in structured interview preparation, even one or two years at a MAANG company can accelerate your trajectory significantly. Many engineers use it as a launching pad, building credibility and savings before moving on to roles that better fit their long-term goals.