Building your career roadmap for FAANG engineering manager roles needs a structured approach and deep planning. FAANG companies hire people with exceptional experience, qualifications, and determination. Candidates must demonstrate a high cultural fit.

The career roadmap for FAANG engineering manager includes building not only technical expertise but also leadership skills.

An engineering manager guides, supports, inspires, and leads a team of technical experts. Having an excellent track record in roles such as motivator, negotiator, conflict manager, and business-savvy leader is important. A career roadmap for a FAANG engineering manager needs a mix of these skills and more.

This blog presents the steps in the career roadmap for FAANG engineering manager roles. The information will help you transition from a senior software engineer to a FAANG engineering manager

Key Takeaways

How to Prepare for the Career Roadmap for FAANG Engineering Manager?

The career roadmap for FAANG engineering manager role starts after graduating with a BS or MS degree in software. The engineering manager requires a few years of experience in managing small to large teams. Exposure to diverse technologies and projects in medium to large-sized IT firms is important.

Let us look at several areas that are important to walk on the career roadmap for FAANG engineering manager that will transform your future.

Tech Stack Portfolio

The career roadmap for FAANG engineering manager role focuses on the tech stacks you have used in your projects. You need to have full expertise in handling, managing, and teaching teams on different tech stacks. Each company also has its own internally developed stack.

FAANG firms also use popular and common tools that other companies use. Demonstrating expertise in their use is an important part of the career roadmap for FAANG engineering manager role. While you may not have used the specific tools, you must have experience with similar tools.

Let us look at the important tools that make up tech stacks.

Tech stack used by the FAANG companies:

• Facebook: React, PHP (HHVM), Python, C++, Java, GraphQL, Cassandra, Flux, MySQL, MariaDB, RocksDB, and Phabricator
• Amazon: Java, C++, Perl, PostgreSQL, and a vast suite of Amazon Web Services such as EC2, S3, RDS, DynamoDB, Redshift for data warehousing, and CloudFront
• Apple: Swift, Objective-C, Python, C++, Scala, Java, iOS, macOS, watchOS, tvOS, Xcode, Apache Hadoop
• Netflix: Python, Java, MySQL, PostgreSQL, React, and its own microservices and frameworks like ZUUL and Eureka
• Google: C, C++, Go, Java, Python, Node.js, and internal technologies like Bigtable, Kubernetes, and its own “PROD” stack

The common tech stack at FAANG companies includes generic software tools that should be in your portfolio. They form important assets in the career roadmap to become an IT engineering manager. Let’s look at some of them below:

• Programming Languages: Python for AI/ML, Java for back-end C++ for performance-critical applications and IoT, Go, Swift, and JavaScript
• Front-end Frameworks: React for building user interfaces
• Databases: MySQL, Cassandra, and Google’s Bigtable
• Cloud Services: Companies use cloud platforms from Amazon Web Services and Google Cloud Platform
• DevOps: Tools like Kubernetes, Jenkins, and GitHub for development workflows

Types of Engineering Managers

Engineering managers work in several functions and focus areas. Your career roadmap for FAANG engineering manager should specialize in a role. However, you can grow into other functions and focus areas, and this step will transform your career.

Engineering managers with experience in multiple focus areas are preferred. FAANG firms expect 5+ years’ experience as a senior software engineer or manager to be considered as a candidate for this role.

The career roadmap for FAANG engineering managers leads to several different paths. Let’s look at some of them:

• Technical Manager: These engineering managers have excellent technical knowledge and have expertise in areas such as coding, architecture, quality, and broad technical expertise.
• Team Manager: To become a team manager, you need to have skills such as prioritizing, driving team growth, recruitment, retention, and creating a growth environment for the team.
• Process Manager: A Process manager optimizes software processes, manages risks, and ensures smooth product delivery.
• Product Manager: A Product Manager strategizes the “why” and “what” of a product, customer research, product strategy, and aligns outcomes with business capabilities.

The career roadmap for FAANG engineering manager can also lead to roles that are based on projects. Let’s look at some such roles:

• Startup Engineering Manager: The career roadmap for FAANG engineering manager with a startup focus needs expertise in operations, setting policies, SoPs, fundraising, and marketing in a startup environment.
• Strategic Engineering Manager: A strategic engineering manager requires experience in long-term technical planning, growth strategies, and driving technological innovation.
• Risk Management Engineering Manager: The career roadmap for FAANG engineering manager with a risk management focus specializes in identifying, assessing, and mitigating technical risks for the company.
• Outsourcing projects: The career roadmap for FAANG engineering manager with an outsourcing focus requires experience in client management, budgeting, stakeholder management, project planning, managing schedules, and milestones.

Education and Certifications for Engineering Managers

Education and certifications are important in the career roadmap for FAANG engineering manager. Typically, a bachelor, or master’s degree from a reputed university in computer science is needed.

Let us look at the education and certifications needed for a career roadmap for FAANG engineering manager roles

Education

• Bachelor’s Degree: A bachelor’s degree in a specific engineering discipline is needed
• Master’s Degree: Master’s degrees such as MS in computer science, MBA, Master’s in project management, and others

Certifications

Graduate certificates in engineering management help to reinforce specialized skills in the career roadmap for FAANG engineering manager roles. Project Management Professional, Certified Scrum Master, Certified Engineering Manager, Certified Systems Engineering Professional, Six Sigma Certifications, Certified Information Systems Security Professional, Certified Solutions Architect, and Certified IT Manager are some of the popular certifications.

Salary and perks of FAANG engineering managers

Engineering managers at FAANG firms are given high compensation. The package can include a high base salary, annual bonuses, substantial stock grants, besides health cover, meals, onsite events, vacations, and other perks.

The salary and benefits should make you determined to build a strong career roadmap for FAANG engineering manager roles. Let us look at the salary and perks of FAANG engineering managers:

• Average total compensation: The average total compensation for an IT Engineering Manager in the United States is $350,000+. This amount can increase based on the location.
• Location: Based on the location, FAANG engineering manager’s salary can vary by the cost of living index. In the San Francisco Bay Area, the total compensation can be between $246,000 – $382,000 per year.
• Company variation: Top companies can offer high compensation. If the qualifications and experience are exceptional, engineering managers can obtain an average total compensation of $1.1 million+
• Comprehensive health insurance: FAANG firms offer health, dental, and vision insurance.
• Stock options and grants: A major portion of total compensation is restricted stock units, which vest over time.
• Retirement plans: FAANG firms offer 401(k) matching and other retirement savings plans.
• Professional development: FAANG firms give access to a large professional network, internal training, and opportunities to attend conferences and events
• Paid time off: FAANG companies offer generous vacation, sick leave, and paid holidays.
• Other benefits: Many companies provide additional benefits, such as wellness stipends, on-site amenities, and tuition reimbursement programs.

Special technologies and systems implemented by FAANG companies

FAANG companies have developed special applications and systems in AI, machine learning (ML), and deep learning (DL). These applications help the firms to offer new services and products. As a part of the career roadmap for FAANG engineering manager roles, it is essential to have a working knowledge of the technologies.

It is good to have experience in these systems, as they stand out in your career roadmap for the FAANG engineering manager role. Working and leading projects with these applications will help you transform your career roadmap to become an IT engineering manager.

FAANG firms offer different services and products, hence the implementation of these technologies and end use will be different. Some FAANG firms use the emerging tech for internal development, while some use it for direct customer services.

Let us look at the special systems that FAANG firms have developed.

AI, ML, Deep Learning at Meta

Meta has developed several applications in AI, machine learning, and deep learning. To strengthen your career roadmap for FAANG engineering manager roles, you should show experience in working with these systems.

Let us look at the emerging tech developed in Meta:

• Artificial Intelligence: With four billion users, Meta drives its value chain with AI systems. These are important to showcase in the portfolio of your career roadmap to become an IT engineering manager.
• Meta AI assistant: The AI assistant is linked in Facebook, Instagram, Messenger, and WhatsApp. It uses natural language conversation, answers questions, makes recommendations, summarizes chats, creates AI-generated stickers, and edits photos.
• Augmented and virtual reality: Reality Labs uses AI to run the metaverse, computer vision for real-time motion tracking in VR products like Meta Quest and smart glasses.
• Content generation: The AI assistant creates unique, high-quality images and text based on simple text prompts. These are used for creative work and marketing.
• Advanced AI models: Meta has developed LLaMA, a large language model (LLM) that runs AI assistants

ML helps AI by using data and algorithms in running tasks. Meta uses ML to personalize and optimize your experience in its platforms. Hands-on experience with ML is an important part of building your career roadmap for FAANG engineering manager roles.

• Ranking and recommendations: ML drives the content-related algorithms for Meta. Some applications are news RSS feed, Instagram feed, and ad delivery. ML helps to predict the content and ads that users like
• Content moderation: With billions of posts made of text, images, and video, Meta uses ML models to automatically detect and filter harmful content, such as hate speech, adult material, scams, and increase safety for users.
• Advertising: Meta obtains revenues mainly from Ads. It uses the Andromeda ML model and a deep neural network to understand and predict ads that users find interesting and engaging. Advertisers then justify their ad spending by reaching target audiences and increasing their return on investment (ROI).
• Security: Meta uses ML to make its platform secure and robust.

Meta uses deep learning with deep neural networks to process large data, identify complex patterns, and apply them to increase the service offerings. Knowledge of deep learning is important in creating your career roadmap for FAANG engineering manager roles.

• Architecture: Deep neural networks of Metas’ deep learning infrastructure help the firm to analyze and process large datasets, find insights, trends, and sentiments
• AI hardware: Meta uses custom-built GPUs such as MTIA to manage the large computational needs of the DL models and accelerate training and inference.
• Self-supervised learning: Meta uses self-supervised learning, where models develop labels from unstructured data. This method helps in developing powerful foundation models like Llama.
• Computer vision: Meta is developing advanced computer vision models, such as the ‘Segment Anything’ model, that cuts out any object in an image with a single click and generalizes to unfamiliar objects.
• Natural language processing (NLP): DL and transformer models are important for NLP tasks. These are important for translation, text classification, and chatbots

AI, ML, Deep Learning at Apple

Apple uses AI, ML, and DL in its products for Face ID, Siri, and camera enhancements, with on-device processing for speed and privacy. These technologies increase personalized experiences, improve accessibility, and boost performance with on-device intelligence and Apple Intelligence with writing tools, image creation, and Siri’s advanced capabilities.

You need to show familiarity with these technologies when developing your career roadmap for FAANG engineering manager roles and transform your future. Let us look at the emerging tech developed by Apple:

When building your career roadmap to become an IT engineering manager, you should be aware of:

• On-device processing: Apple uses machine learning models in devices through the Neural Engine chip. The process increases fidelity, speed, and privacy since data is processed locally and not sent to servers.
• Apple Intelligence: In this system, Apple has integrated generative AI into the core operating systems. Apple devices can perform system-wide writing tools, image generation, such as Genmoji, Image Playground, and enhanced Siri capabilities.
• Accessibility: Apple uses AI to build features making devices easier to use with tools like Voice Control, Live Captions, and Sound Recognition

Apple has several products, and each has special functionalities. While building your career roadmap for FAANG engineering manager roles, you must show expertise in:

• Camera and photos: Apple uses deep learning models for features like Smart HDR, Deep Fusion, and automatically creates mini-movies from the photos and videos by recognizing scenes and subjects.
• Health and fitness: Apple uses AI to study data from the Apple Watch and iPhone to track metrics like heart rate, sleep, and activity. It then gives personalized insights, health alerts, and custom fitness plans.
• Siri: Apple uses this voice assistant with advanced speech recognition and NLP to understand user requests.
• Face ID and security: Apple uses deep learning for facial recognition to enable secure unlocking and authentication.
• Device performance: Apple devices use AI to manage battery life, switch between Wi-Fi and cellular networks, and optimize device performance.
• Apple Maps: Apple uses AI for predictive destination suggestions and identifying where your car is parked.
• Personalization: Apple uses ML algorithms to bring news with personalized recommendations based on user behavior and preferences.
• Developer tools: Apple has released developer tools to the general public. It encourages them to use the tools and create applications. Knowing these tools is important in developing your career roadmap for FAANG engineering manager roles.
• Core ML: Apple gives developers access to the framework so that they can integrate machine learning models into their apps.
• Custom models: Apple encourages developers to train and customize models with their own data and add new intelligent features to their apps.

AI, ML, Deep Learning at Amazon

Amazon uses AI, machine learning, and deep learning in customer-facing features like product recommendations, voice assistants, and backend functions such as supply chain optimization, fraud detection, and warehouse automation. These technologies help Amazon to increase customer experience, improve efficiency, and reduce costs. It is essential to know these technologies to build a robust career roadmap for FAANG engineering manager roles.

Let us look at various implementations at Amazon:

• Customer services: Amazon uses AI, ML, and DL to enhance customer experience in many ways. It is important to have hands-on experience in these implementations as a part of your career roadmap to become a FAANG engineering manager.
• Personalized recommendations: Amazon studies your browsing and purchase history to recommend relevant products.
• Alexa: This is a voice assistant that uses deep learning for speech recognition, text-to-speech, and natural language processing to accurately respond to voice commands.
• Amazon Go stores: Amazon uses computer vision, sensors, and deep learning with the ‘Just Walk Out’ system that automatically charges customers for purchased items
• Image search: Amazon uses AI to help customers search for products with images.
• Chatbots: Amazon has implemented machine learning chatbots to provide customer support.
• CodeWhisperer: Amazon uses this generative AI app to assist developers in faster coding
• Operations: Amazon intensely uses AI, DL, and ML to run the back-end operations. It is important to know about these applications to build your career roadmap for FAANG engineering manager roles
• Supply chain: Amazon uses machine learning for demand prediction, inventory management, and for delivery routes. The process helps in faster delivery and lower costs.
• Warehouse automation: Amazon uses AI and robots in fulfillment centers. This tech helps in sorting packages with machine vision and checking inventory for faster operations.
• Fraud detection: Amazon uses machine learning for analysis of transactions to identify malicious activity and help in protecting customers and merchants.
• Predictive maintenance: Amazon uses machine learning to predict when the facilities need maintenance, thus reducing downtime.
• Packaging optimization: Amazon uses computer vision and deep learning for analysis of products and finds the most efficient and sustainable packaging, reducing waste.

AI, ML, Deep Learning at Google

Google has developed its own AI, machine learning, and deep learning systems for its products and services. You should know about these implementations to create a career roadmap for FAANG engineering manager roles.

These technologies are used in Google’s platforms, voice assistants, autonomous driving systems, and Google Cloud tools. Let us look at how Google uses these systems:

• Artificial Intelligence (AI): Google uses AI to run the Google Assistant, which understands and responds to voice commands. It uses generative AI to simplify information processing for users.
• Machine Learning (ML): Google uses ML in its network to learn from data without programming.
• Google Ads: Google’s machine learning algorithms help to analyze user data like search history and location to provide relevant ads. The system also optimizes bidding based on performance.
• Google Cloud: Google uses this application to provide tools and infrastructure for developers to build and host their own ML models. It offers pre-installed frameworks like TensorFlow and PyTorch, and AutoML to help build models for images, video, and text without extensive coding.
• Deep Learning: Google uses DL in several ways to provide enhanced services. Some of the applications are:
• Google Search: The Google RankBrain, a deep learning system, helps the search engine to understand the intent behind queries and deliver more accurate results.
• YouTube: Google uses deep learning to study viewing habits and provide personalized video recommendations to users.
• Google Photos: Google uses deep learning for image recognition, identifying objects, faces, and text within photos.
• Self-driving cars: A radical technology, Google uses deep learning algorithms for autonomous vehicles to see and react with their surroundings.
• Robotics: Google uses deep learning to help robots learn tasks such as grasping objects and pouring liquid by analyzing data from experiences, simulations, or video demonstrations.

AI, ML, Deep Learning at Netflix

Netflix uses AI, machine learning, and deep learning in several ways. It is important to know these applications on your quest to build a career roadmap for FAANG engineering manager roles. Netflix uses the technologies in the recommendation engine, personalizing user experience, optimizing streaming quality, and informing content production.

The technology analyzes user data like viewing history and ratings to recommend content, personalizes thumbnails. It uses algorithms to predict internet speeds and cache content for better streaming. Machine learning is also applied to understand content, create subtitles, and improve creative tools.

Understanding the applications is critical in building your career roadmap for FAANG engineering manager roles. Let us look at the implementations at Netflix:

• Recommendation engine: Netflix’s recommendation engine uses AI, providing 80% of its streamed hours.
• Data analysis: Netflix uses machine learning models to analyze user data, watch history, ratings, pauses, and search queries, to create a profile of their tastes.
• Collaborative filtering: This system helps to identify patterns by looking at similarities between users and the content they watch.
• Content-based filtering: Google uses this system to analyze attributes of the content, genre, actors, and plot.
• Deep learning: Google uses deep learning models to find complex data patterns for precise recommendations.
• Personalized thumbnails: Google uses AI to select thumbnails to show for a show or movie based on a user’s preference to increase the likelihood they will click on it.
• Streaming and content optimization: The Netflix system refines itself by using techniques like A/B testing and reinforcement learning to refine algorithms and keep recommendations fresh.

Understanding these systems will enhance your career roadmap for FAANG engineering manager roles. Some ways Netflix improves streaming are:

• Streaming quality: Netflix uses AI algorithms to predict internet speeds at different times to decide on content caching on regional servers, ensuring a smooth viewing experience.
• Content production: Netflix uses machine learning to obtain insights into content trends and to create assets for new content.
• Subtitling and translation: Netflix uses Natural Language Processing and the BERT model for analyzing and creating subtitles, understanding textual data like reviews and descriptions.
• Subscription abuse prevention: Netflix uses AI for analysis of device and geolocation data, IP addresses, and user behavior patterns to detect and prevent subscription sharing and protect its revenue.
• A/B testing: Netflix runs tests to experiment with different algorithms and strategies, with the goal of improving user satisfaction and engagement.

Learn from Experts

Building your career roadmap for FAANG engineering manager roles requires more than just technical knowledge — it demands structure, strategy, and confidence. That’s exactly what you’ll gain from Interview Kickstart’s Engineering Manager Masterclass.

This 4-month intensive course helps you master data structures, algorithms, system design, and key machine learning concepts like supervised and unsupervised learning, deep learning, and reinforcement learning. You’ll spend 10–12 hours per week building the depth and clarity needed to excel in FAANG-level interviews.

The program also includes a 3-week career coaching module, where FAANG+ instructors guide you through resume building, LinkedIn optimization, and salary negotiation. Plus, you’ll receive 6 months of post-program support, featuring 15 mock interviews and 1:1 mentorship with hiring managers from top tech companies.

By the end of this masterclass, you’ll have the technical skills, interview readiness, and confidence to land your dream engineering manager role at FAANG or any top-tier company

Conclusions

The blog presented several key aspects of building your career roadmap for FAANG engineering manager roles. While you have the experience and qualifications, confidence and presentation skills are also important. Interviews are tough, and you need expert guidance to help you crack the questions.

The career roadmap for FAANG engineering manager roles requires a high level of preparation, study, experience, and knowledge of emerging technologies used. The blog provided insights into these stages and also discussed several areas and applications of emerging technologies used by FAANG firms.

However, this is the starting point of the career roadmap for FAANG engineering manager roles. At Interview Kickstart, we have several domain-specific experts who have worked for Meta and FAANG.

Let our experts help you build your career roadmap for FAANG engineering manager roles. You have much better chances of securing the coveted job.

FAQs: Career Roadmap for FAANG Engineering Manager Roles

Q1. What is the method to prepare the career roadmap for FAANG engineering manager roles?

The career roadmap for FAANG engineering manager roles requires some years of experience in leading projects. You need to show your expertise in multiple areas of technology. Revisit your projects and the technology aspects, and prepare use case stories.

Q2. Do we have to show coding expertise in the technical rounds?

Yes. A high level of knowledge about deep learning algorithm models, data science, and AI is needed. You will be a part of technical experts and build solutions with emerging tech.

Q3. Do we need to have certifications?

Certifications certainly help to reinforce your skills and expertise. Study the job requirements to know the details of qualifications, experience, and certifications.

Q4. What other preparations are needed to build the career roadmap for FAANG engineering manager roles?

At Interview Kickstart, we have a structured training course on preparing for different roles. The details are given in the ‘Learn from Experts’ section.

Q5. Whom should I approach if I have some questions after I finish the course?

Once you register for the Master Course for Engineering Manager, we provide support for 10 months.

References

1. Emerging Technologies and Trends for Tech Product Leaders
2. Examples of Artificial Intelligence (AI) in 7 Industries
3. Salary of Engineering Managers in the US