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Faang Companies Jobs (NOW HIRING)

Zania, Inc

Applied AI Engineer

Palo Alto, CA · On-site

$180K - $250K/yr

FAANG companies, Big 4 firms, and a portfolio of the world's most notable enterprises. * Tier 1 Backing: Series A led by NEA, with Anthropic and Menlo Ventures. $18M raised to build a generational ...

Staffingine LLC

Frontend Engineer

New York, NY · On-site

... FAANG (refer to target companies list) * Product-​minded and has worked on customer-​facing products * Worked closely with design to build polished,​ high-​performance UIs -- and aren't ...

MM International

QA Engineer

Redmond, WA · On-site

Experience at FAANG, Magnificent 7, MANGO , or other leading technology companies * Demonstrated longevity in prior roles Role Details * Location: Onsite - Redmond, WA * Schedule: Monday-Friday, 40 ...

Reducto

Legal Counsel

San Francisco, CA · On-site

$200K - $250K/yr

We've grown rapidly, increasing revenue 8x year over year and partnering with hundreds of companies, from leading AI teams like Harvey, Vanta, and Scale, to enterprise customers across FAANG and top ...

Anam

GTM

New York, NY · On-site

Our team comprises top technical talent from frontier AI labs and FAANG, led by ex-Synthesia (AI ... Anam drives measurable outcomes for customers from Fortune 500 companies to AI-native hypergrowth ...

AI Talent Now

Senior Product Engineer

Palo Alto, CA · On-site

$140 - $250/hr

Background in well-known tech companies or startups * Comfortable working closely with internal ... tech (e.g., FAANG, Bloomberg, NVIDIA), VC-backed startup, or as founder * Has conducted code ...

Meticulous

GTM Operator

San Francisco, CA · On-site

$60 - $120/hr

What we do We're building the last piece of the puzzle to help companies unlock AI code generation ... You have been in rooms with decision makers at MBB / Tier 1 bank / FAANG and are now eager to ...

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How much do faang companies jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for faang companies in the United States is $53.14, according to ZipRecruiter salary data. Most workers in this role earn between $42.31 and $66.59 per hour, depending on experience, location, and employer.

What is the difference between Faang Companies vs Software Engineers?

AspectFaang CompaniesSoftware Engineers
Required CredentialsBachelor's or higher in CS or related field, often with advanced degreesBachelor's or higher in CS or related field, certifications vary
Work EnvironmentFast-paced, innovative, collaborative teams, high-performance cultureTechnical, project-focused, team-based, often in office or remote settings
Employer & Industry UsageLeading tech giants like Facebook, Apple, Amazon, Netflix, GoogleProfessionals working in software development across various industries

Faang Companies are top-tier tech firms known for their competitive environment and innovation, while Software Engineers are professionals working in diverse industries, including but not limited to Faang. The roles often require similar credentials, but Faang Companies offer specific opportunities and culture that distinguish them from general software engineering roles.

What are FAANG companies?

A FAANG Companies job refers to a position at one of the top five major U.S. technology companies: Facebook (now Meta), Apple, Amazon, Netflix, and Google (now Alphabet). These companies are known for their competitive hiring processes, high salaries, and strong benefits. Jobs at FAANG companies range across engineering, product management, design, marketing, and other fields. Employees often work on cutting-edge technology and large-scale products that impact millions of users. Due to their prestige, FAANG jobs are highly sought after by professionals in the tech industry.

What are the key skills and qualifications needed to thrive at a FAANG company, and why are they important?

To thrive at a FAANG company, you generally need a strong background in computer science, problem-solving abilities, and a relevant degree or equivalent experience. Proficiency in programming languages (such as Python, Java, or C++), familiarity with distributed systems, and experience using development tools like Git are typically required. Exceptional communication, collaboration, and adaptability help candidates excel in dynamic, cross-functional teams. These skills and qualities are vital to deliver innovative solutions and succeed in a fast-paced, high-impact environment.

What are some common challenges faced when working at FAANG companies, and how can new hires effectively overcome them?

New hires at FAANG companies often encounter challenges such as adapting to fast-paced environments, navigating complex organizational structures, and managing high expectations for performance and innovation. It's important to proactively seek feedback, communicate openly with your team, and take advantage of mentorship programs or onboarding resources. Building relationships across departments and continuously updating technical or soft skills will help you integrate more smoothly and contribute effectively to your team.
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Faang Companies jobs near you
Infographic showing various Faang Companies job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 16% Part Time, 5% Contract, and 1% Nights. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution, with an average salary of $110,528 per year, or $53.1 per hour.

Applied AI Engineer

Zania, Inc

Palo Alto, CA • On-site

$180K - $250K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted yesterday

Job description

Why Zania
Every enterprise spends millions on Governance, Risk, and Compliance. It's one of the most critical - and most painful - parts of running a business. The industry has been dominated by legacy platforms with notoriously low NPS scores for decades. It's completely ripe for disruption.
Zania is building agentic AI for GRC to solve this problem. We're building intelligent agents that execute complex risk and compliance workflows with full explainability - not dashboards, not copilots, but agents that do the work. We've found exceptional product-market fit and are scaling fast.
Why join:
  • Dream Customers: FAANG companies, Big 4 firms, and a portfolio of the world's most notable enterprises.
  • Tier 1 Backing: Series A led by NEA, with Anthropic and Menlo Ventures. $18M raised to build a generational company.
  • World-Class Team: AI and security leaders from Airbnb, Microsoft, Bain, Deloitte, PwC, Brex, and Instacart.
  • Pioneering Technology: Our engineers and GRC experts work at the absolute forefront of applied AI, building agentic systems that will define the future of compliance.
  • Hyper-Growth: 10x ARR growth in the last year.
  • Competitive Compensation & Equity.

The role
You will build AI systems designed to outperform the world's leading experts in Governance, Risk, and Compliance. Not research. Not prototypes. Production systems with a fanatical focus on accuracy, explainability, and responsible design. You will own the AI-native products that set a new global standard for GRC.
We use an in-person work model and offer relocation assistance.
What you'll do
  • Build & fine-tune models. Fine-tune foundation models on proprietary data and implement novel techniques to achieve world-class accuracy on complex GRC tasks.
  • Develop AI-native workflows. Build sophisticated, multi-step agentic workflows that automate complex GRC processes - from risk assessment to compliance monitoring to evidence collection.
  • Champion responsible AI. Implement and pioneer methods for AI explainability and safety. Our systems must be transparent, auditable, and fair. This is non-negotiable in our domain.
  • Drive innovation. Rapidly prototype, evaluate, and integrate state-of-the-art research (agents, RAG, new architectures) into reliable, production-grade features.

Representative projects
  • Build an AI agent that analyzes thousands of regulatory documents and internal controls, identifying compliance gaps with higher accuracy than a team of human experts.
  • Develop an explainable AI system for risk assessment, allowing auditors and executives to understand and trust the AI's reasoning on high-stakes decisions.
  • Build an advanced RAG pipeline over a massive corpus of unstructured company data to produce precise, verifiable assessments against complex compliance requirements.
  • Partner with GRC subject matter experts to create ground-truth datasets for tasks like third-party risk evaluation, then fine-tune models that become the industry standard.

What you have
  • 3+ years in an applied AI or machine learning engineering role.
  • Proven product sense. You've shipped reliable, production-scale ML products. You know how to use offline evaluation and online experimentation to achieve high-performance results.
  • Hands-on applied AI expertise. Direct experience building with LLMs - fine-tuning, RAG, and agentic systems. Not theoretical. You've put these into production.
  • High agency. You take full ownership of outcomes, move with a bias for action, and have a relentless drive for world-class accuracy. You see constraints as design problems, not blockers.
  • Strong communication. You can work closely with security and GRC research counterparts and articulate technical tradeoffs clearly.

Minimum Qualifications
  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
  • 3+ years of experience in applied AI, machine learning engineering, or a related technical role
  • Demonstrated hands-on experience building and deploying LLM-based systems (fine-tuning, RAG, or agentic workflows) in a production environment
  • Strong written and verbal communication skills - you will collaborate closely with GRC subject matter experts and must translate technical tradeoffs clearly to non-technical stakeholders

Compensation & benefits
  • Competitive salary + significant equity
  • Flexible PTO
  • Medical, dental, and vision insurance
  • Meals and snacks in the office
  • Relocation and immigration support

Zania is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.

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