AI Architect

In this career guide, you’ll learn everything you need to know about Artificial Intelligence as a career, from roles and responsibilities, to work environment and roadmap to becoming an AI Architect.

Who's an AI Architect?

Information technology and data science are now integral functions in all organisations. AI architects deal with information and provide AI-powered solutions to support an organisation’s current and future needs.

The AI architect’s role is similar to that of a chief data scientist. In this field, you are required to work with various types of technologies, choose the right one to achieve solutions to the organisation’s problems, and implement those solutions, thus building an architecture that can work in the present and be adapted for future use.

What
Responsibilities

What will you do?

Understanding Client’s Problems

First and foremost, your job as an AI architect will have you facing clients directly, understanding their problems. Only by carefully analysing their needs can you provide suitable AI-powered solutions to their issues.

Example: Say for instance your client has an eCommerce business. They wish to establish a 24-hour customer support service system. Now, you need to assess this problem and think of a solution.

Providing Tangible Solutions

The AI architect’s primary job is to provide their clients solutions to various problems using the frameworks of AI-powered technology. You will be responsible for choosing the right technology that enables you to plan the implementations of solutions.

Example: Here, you assess the client’s pain points and suggest a solution. For instance, you can suggest an AI-powered 24-hour chatbot service for the eCommerce website.

Evaluating Escalations

While choosing the AI-powered technology that solve your clients’ problems, it is essential that you evaluate the future adaptability of the technology. The solutions must not only work in the present but also deal with any complexities the client might face in the future.

Example: You need to check whether the chatbot solution you offered is fool-proof, sustainable, and will operate without glitches.

Managing Data Architecture

As an AI architect, it is pertinent that you have vast knowledge about artificial intelligence, its tools and technologies, as well as the requirements and restrictions of its framework. This enables you to manage data and remain up-to-date with the evolving trends.

Example: You must be aware of the know-hows of chatbot technology, need for updates, bug fixes, etc. to provide hassle-free services to your clients.

Collaborating with Technical Teams

You may be required to coordinate with data scientists and business analysts or collaborate with the design, development, and engineering departments to ensure that the proposed technology is implemented and there are no glitches in the solutions to your clients’ problems.

Example: Here, you need to ideate and implement the chatbot solution with the help of various other teams such as the graphic design, software development, consumer support team. This is to ensure seamless implementation of the AI-backed solution.

Workplace

Where will you work?

Office

AI architects are mostly required to work in an office space to make it easier to collaborate with other departments. Tech offices are usually very attractive and creativity-inducing. Moreover, you may even be allowed business casuals if the company does not follow a strict formal dress code.

Education

How do you get there?

This stream won’t help you make an entry into this field.

This stream won’t help you make an entry into this field.

STEP 1: Class XI-XII/Junior College

A foundation in subjects like physics and computer science helps you carve a career in AI. Thus, you must pursue the Science stream in 11th to kickstart your career as an AI architect. Additionally, you can opt for extra-curricular online classes to learn programming languages like C++ to get an understanding of the algorithms.

STEP 2: Graduation

After completing 10+2, you can choose to get a graduate’s degree in computer science, information technology, mathematics and statistics, finance, or economics. Almost all of these courses last for a duration of three years. The most common undergraduate courses are the Bachelor of Technology in Computer Science Engineering (B.Tech CSE) and the Bachelor of Engineering (B.E.).

STEP 3: Post-Graduation

While a Bachelor’s degree is enough to land you an entry-level position as a programmer, you can also opt for a Master’s or Ph.D. that offers advanced computer science education with a specialisation in artificial intelligence or directly go for M.Sc. or M.Tech in AI.

STEP 4: Internship

If you land an internship as a programmer, you can take up machine learning courses on the side in order to understand algorithms better and start coding. Ideally, opt for an internship in an IT firm, where you can get hands-on training from experts.

STEP 5: Land a Job

More than 50% of Indian companies recruiting for AI job roles seek candidates with more than five years of experience. Start with coding, gain the necessary programming skills, and move on to data science and machine learning. Stay up-to-date with the latest technologies and enhance your communication skills and business knowledge along the way.

What skills would you need?

Critical thinking

Critical thinking

Marketing strategies involve a lot of trial and error. You will come up with a lot of ideas that sound great on paper. When you analyse them, you might learn that they can’t be executed as per the budget. You should be able to look at an idea practically and see if it will serve its purpose.

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Promotion levels

How do you make it to the top ranks?

Scope

Pursuing your career locally VS abroad

A career in AI requires exceptional knowledge of mathematics, physics, computer science, engineering, as well as specialised skills in machine learning and NLP. While you pursue a graduation in any of these subjects, it is important to enrol for external courses that teach you more about AI and machine learning. Most graduation courses in B.Sc. are for three years while B.E. or B. Tech. courses go on for a duration of four years, with course fees ranging from INR 50000 per year to 5 lakhs, depending on your course and college. Since the role of an AI architect is a top-level job, it is also important you pursue a Master’s degree in your subject that goes on for another three-four years, costing an additional fee of up to INR 5 lakhs. Some professionals also choose to pursue a Ph.D. for a higher salary, with course fees starting from INR 10,000 to 3 lakhs. Getting into the field of AI takes another four-five years of working experience, so you can presume that you will reach your goal of becoming an AI architect way into your thirties.

There are lucrative career opportunities in AI and machine learning abroad. AI architects command a high salary that can go well above $100,000. However, becoming an AI architect takes over 10 years of work experience in AI. Professionals in this role have a minimum of a Master’s degree in data science with focus on big data and analytics, or computer science with advanced knowledge of programming languages like Python, or mathematics with focus on statistics, probability, logic, calculus, and algorithms. Alternatively, you can also opt for a degree in physics, engineering, or robotics and upskill to AI. Online channels like Udacity offer courses in artificial intelligence and deep learning while Coursera provides courses in machine learning. These courses are conducted for three to four months, with fees that range from INR 20000 to INR 25000 per month. Additionally, you can improve your resume working with open-source AI research groups that are available on GitHub or participate in Google’s data community called Kaggle.

 

Payscale

How much would you get paid?

Your salary in AI will depend on your role and the variations of your tasks. In the last few years, careers in this field have peaked due to the growing demand for AI and the digitisation automation of most industries. The need for AI skills have doubled and job postings have also increased.


Specialisations

What are your career options?

AI Programmer

AI programmers build operating software that can be used in artificial intelligence programmes or applications. They work closely with data science teams, automating the infrastructure used by them as well as converting machine learning models into APIs so that other applications can access them.

Data Scientist

Data scientists collect, clean, analyse, and interpret large and complex datasets to derive business insights. They work closely with AI professionals to leverage machine learning and predictive analytics for their analysis.

Machine Learning Engineer

Machine learning engineers feed the data defined by data scientists into predictive models. Like AI scientists and architects, they work with vast knowledge and understanding of machine learning algorithms, deep learning algorithms, and deep learning frameworks.

Business Intelligence Developer

Like AI architects, these professionals are also responsible for research and providing solutions for the organisation or client’s problems. For this, they design, model, and analyse large amounts of complex data to identify business and market trends, and derive insightful solutions.

You’ve only scratched the surface.

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