The demand for architects in the field of artificial intelligence (AI) is growing. AI architects play a key role in designing and implementing AI solutions by using their information technology, computer programming, and software design skills.
If you’re thinking about becoming an AI architect and you’re wondering what you need to learn to prepare for success in the field, you’ve come to the right place. This article will provide a detailed roadmap to help you understand what you’ll need to learn and how to prepare for work as an AI architect. We’ll also discuss potential salaries as an artificial intelligence architect and the projected job growth within the industry in the coming years.
Table of contents
- What is an AI architect?
- Skills required for AI architects
- How to become an AI architect
- How much do AI architects make?
- Job outlook for AI architects
What is an AI architect?
AI architects build AI systems to address a wide range of problems. They have a vast knowledge of AI algorithms and frameworks that they use to bridge the gap between data scientists, engineers, and developers to ensure their solutions run smoothly.
Key responsibilities of an AI solutions architect include:
- Interdepartmental teamwork. This role isn’t completely independent and requires collaboration with other professionals to adapt and improve digital products.
- Technology development. Beyond meeting today’s needs, AI solutions architects must align implementation of technology with both current and future requirements.
- Solution implementation. Creating effective AI tools requires defining the desired outcome of AI systems and incorporating the appropriate technologies.
- Monitoring results. Auditing tools and software across the board produces continual improvement.
- Risk management. AI architects work alongside security and risk management officers to identify and overcome potential risks.
As AI systems and software continue to expand and diversify, AI architects are becoming increasingly important. AI architects play a key role in streamlining the development and operation of AI products.
Companies that employ highly skilled and knowledgeable AI architects will have an easier time collaborating with stakeholders across the organization and building a strong and effective AI architecture.
Skills required for AI architects
AI architects should have a combination of nontechnical and technical skills, including knowledge about the following topics:
- AI architecture. AI engineers should understand how machine learning (ML) and deep learning contribute to pipeline architecture workflows. They should also understand the various components of model building, production, and deployment workflows.
- Natural language processing (NLP). Familiarity with NLP is vital because of the overlap with machine learning and the ability of NLP to improve data analysis and streamline processes.
- Data management. A big part of an AI architect’s job will involve data management, which is the practice of gathering, storing, and using data securely and effectively.
- Data science. In addition to familiarity with advanced tools like Python and SAS, AI architects should know how to incorporate ML techniques like random forest and neural networks along with frameworks such as TensorFlow.
- Infrastructure and operations. Your AI infrastructure includes all the hardware, software, and networking tools involved in your AI projects. This is the backbone of your network and, as an AI engineer, you should understand it fully.
- Software engineering and DevOps. DevOps is a collection of beliefs and tools that enhance an organization’s capacity to build AI applications and deliver services at a high speed.
An AI architect’s contributions don’t end at their technical skills. Important nontechnical skills for AI architects include communication skills, project management, and collaboration. AI architects collaborate with stakeholders involved in different stages of the project and oversee many different facets of AI product development.
These attributes ensure that AI architects can effectively convey technical information to nontechnical stakeholders, manage project timelines and resources efficiently, and foster a cooperative environment among different teams, which drives the successful completion and quality of AI projects.
How to become an AI architect
While becoming an AI architect will take several steps, the process is easier once you understand what’s involved. Let’s break each one down in detail below.
1. Acquire the necessary educational background
Typically, AI architects have a strong foundation in computer science or a related field. A bachelor’s degree is often seen as the minimum requirement since your work will require an in-depth awareness of programming and data science.
Some AI architects will continue their studies and work toward a master’s degree in artificial intelligence or data science to further enhance their knowledge and expand their career prospects.
2. Learn programming languages
AI architects need to be able to work with programming languages like Python and Java in order to understand and implement the algorithms that are foundational to AI. AI architects often use these languages in AI development and machine learning algorithms.
Several excellent programs and certifications exist to help you learn the fundamentals while giving you a credential to help you stand out to potential employers.
3. Dive into data science and machine learning
Data science and machine learning play key roles in the field of artificial intelligence. Machine learning enables computers to learn and improve without direct instruction or programming, and insights from data science help AI improve its decision-making and operations. To best incorporate this information, AI architects must understand data structures, big data, and data analysis.
If you want to enhance your understanding in any of these areas, consider enrolling in a specialized course or pursuing a certification that will attest to your proficiency in these concepts.
4. Master AI frameworks and tools
TensorFlow and PyTorch are both important frameworks to learn if you’re preparing to become an AI architect. Like TensorFlow, PyTorch is useful when building deep learning models and speeding up production development after research and prototyping.
You should also be aware of AI tools like Amazon Web Services (AWS) and Microsoft’s Azure that help with cloud computing and scaling AI solutions. Software like Tableau and Sisense is also helpful for enhanced visualization and converting raw data into pipelines.
Online classes and certifications cover many of these tools if you want to gain additional exposure before entering the workforce.
5. Gain real-world experience
Although classes, books, and online how-to guides are helpful, there’s no replacement for hands-on experience. To prepare for your career path in AI architecture, you’ll benefit from pursuing internships, entry-level positions, or freelance work as an AI engineer or data analyst. Upwork is a great source to check for open freelance roles and potential projects that you can submit a proposal to work on.
As you work on different AI projects, you’ll build up a strong portfolio that you can share with potential employers to show off what you can do. Teaming up with other AI professionals and completing joint projects together is another excellent way to build your skills and expand your knowledge.
6. Develop soft skills
Soft skills like communication and problem-solving are as important to developing a career as an AI architect as any technical skill. If you can gain greater competencies in these areas, you’ll be able to effectively collaborate with other stakeholders and explain the work you’re doing with both tech-savvy and nontechnical audiences. Soft skills benefit you when managing projects and communicating with stakeholders about the status of ongoing efforts.
If you’re looking for ways to build your soft skills, start by identifying the most important traits you would like to develop. You can’t work on everything at once, so clarify your priorities and define your end goal.
From there, you can solicit feedback from friends and colleagues, pursue online courses and resources relevant to the skill you’re developing, and look for hands-on opportunities (such as a new leadership role) to sharpen those skills in a real-world setting.
7. Obtain certifications
Perhaps you don’t have a degree in computer science or engineering. Maybe you only have a bachelor’s degree, and you’re wondering how you can further stand out on job applications without spending the time (and money) necessary to get a master’s degree.
Online courses help level up your knowledge and boost your credibility among prospective clients and employers. Consider enrolling in a class on AI technology, machine learning models, or software development.
Some of the most popular online certification courses and platforms include:
- Coursera. With over 150 options to choose from, including courses like “AI for Everyone” and “Introduction to Artificial Intelligence,” Coursera is an excellent option for both beginners and more seasoned professionals.
- Stanford University. Stanford offers an online Artificial Intelligence Graduate Certificate that students can complete within one or two years by setting aside 15-20 hours per week.
- IBM. If you’re looking for a general introduction to AI topics that won’t break the bank, IBM’s free AI engineering course is a great option. The same is true for IBM’s Applied AI Professional program.
- Microsoft. Microsoft offers an Azure AI Engineer Associate certification along with an Azure Data Science Associate course that walks you through the process of setting up a cloud environment to work with AI models.
8. Keep up with advancements and networking
The field of artificial intelligence continues to change and evolve, and people working in the field need for their skills to stay relevant.
You can keep yourself informed by browsing online forums, following related social media accounts, and attending conferences to learn from industry experts and network with fellow professionals. Consider contributing to open-source projects and performing academic research for a community such as Kaggle.
How much do AI architects make?
AI architects tend to be compensated well due to the current high demand and the unique, specialized skill set required by the job. However, as you can imagine, average salaries can range based on location, experience, and industry.
According to the Bureau of Labor Statistics (BLS), database architects earn a median wage of around $135,000 each year. If you’re making less than $75,000, you’re likely in the bottom ten percent of industry averages. However, the top ten percent can exceed $197,000 annually.
Database architects working in computer design or infrastructure tend to command higher pay, while someone working in company or enterprise management may have a lower average.
Database architects are more prevalent in states such as Colorado and Virginia, where employment exceeds 1.6 per 1,000 jobs. California’s database architects command an annual wage of $152,960, which is the highest in the country. Workers in Texas are only a few thousand dollars behind, with a median annual salary of $146,970.
Job outlook for AI architects
The importance of artificial intelligence is growing in many industries from health care to robotics. This increased interest in AI will further boost the need for qualified AI architects.
Employment of database administrators is projected to grow by 7% by the year 2032. Currently, there are around 85,000 database administrators employed in the United States, and this number is forecasted to grow to 91,200 by 2032. The end result is around 600 new job openings each year, some of which will be necessary to replace workers who retire or transition to other fields.
Find AI architect jobs on Upwork
While becoming an AI architect is a journey that requires many steps, it’s definitely something that you can do if you’re willing to be patient, take the right steps, and build the necessary skills to set yourself up for success.
If you’re thinking about getting started, consider signing up for a free online course or talking with a professional currently in the field to ask questions and learn more about what you can expect if you move forward.
You can also browse the AI jobs currently open on Upwork. Upwork offers a large database of open full-time and freelance positions, including many in the field of AI. Check out Upwork today to learn more about how you can get started in your new career in AI.
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