As the new field of artificial intelligence sets out to build glorious and gleaming castles of pure logic and reason, great debates are underway. Philosophers, computer scientists, and lawmakers are all wondering how these new creations can be made safe for society. Reliability is paramount. So is security. And now, for the first time in the history of computation, steps have to be taken to make sure AI has motivations and goals that are aligned with those of its users.
With enormously complex artificial neural networks behind it, and vast training sets of data that cannot be validated by hand, these are pressing questions without clear answers.
But in the broader field of software engineering, there is well-established precedent for ways to design and build products in ways that achieve those goals. Applying a similar set of principles to the development of artificial intelligence is the domain of a new kind of professional – the AI architect.
What Is an AI Architect?
Architecture – in AI as in coding in general – is a specialized role in the software development process.
As software systems grew larger and larger, sometimes into hundreds of thousands of lines of code and multiple subsystems and modules, developers could no longer simply dive in and build an application from end-to-end. For the purposes of avoiding conflicts, coordinating multiple teams, and ensuring efficiency in the design process, they needed a plan.
Just as buildings are developed as a set of blueprints long before ground is broken for the foundation, software architects plan application programs before coding ever starts.
Putting together those plans turns out to be a specialized job in itself. The role of software architect was born.
Artificial intelligence is, if anything, enormously more complex than even the most complex software programs in use today. So it’s clear to see how the field needs similar AI solution architects to design systems effectively.
AI architects are typically senior programmers who are responsible for taking a big-picture perspective of an end-to-end software solution and designing the connections, resources, and modules necessary to build it efficiently.
What Is a Typical AI Architect Job Description?
AI architecture is by default a kind of leadership position in the universe of AI careers. In these positions, you’ll be asked to:
- Set technical visions and goals, and outline achievable roadmaps to attaining those goals
- Work with other teams including stakeholders and outside business partners to identify tools, inefficiencies, and agree on objectives
- Design software systems and break down the work process into parts that can be assigned out to teams
- Analyze component options to determine build versus buy decisions and explain tradeoffs to leadership
- Troubleshoot various obstacles and bottlenecks that may arise during development
Tied to all these tasks is the necessity to keep up with the latest developments in AI and related software fields. AI architect jobs may revolve around AI systems themselves, but they may also involve integrations with other software and systems. It’s not unusual for employers to look for architects who are not only well-versed in AI, but also have strong subject-matter expertise in related fields.
AI Architect Jobs Aren’t Yet Standardized
In addition to the standard AI architect job listings, you’ll find such positions under a variety of other titles today:
- Senior Data Architect
- System Architect Director - AI Implementation and Innovation
- Generative AI Architect
- AI Software Architect
- Solutions Architect, Cybersecurity AI
And, of course, many typical software architect positions will be incorporating more and more AI architecture responsibilities within them. The job titles aren’t likely to change, but the job descriptions will. So you’ll have to read carefully as you are on the hunt for AI architect positions.
How to Become an AI Architect
Not just anyone is up to the challenge of software architecture in general. The qualifications and abilities to become a successful AI architect are even stricter.
For starters, AI architects need to have some deep background skills in what makes AI tick. Just like real-world architects need to understand the material properties of the beams and supports in their designs, an AI architect must have solid knowledge of the systems they are building on.
That almost always means an advanced education in AI and computer science. And it’s common for companies to demand years of on-the-ground experience as an AI developer or programmer.
Architects of AI need soft skills as well as hardcore coding skills and scientific knowledge, though. Since they are usually building toward the vision of other stakeholders, strong writing and interpersonal communication talent is needed. They may also crossover into project management roles. That means learning the tools of the trade for keeping teams on track and in touch.
AI Architect Salary Levels Bump up the Programmer Averages
An AI architect is really just a senior, specialized kind of developer. So when looking for the average salary levels for the role, we can turn to the Bureau of Labor Statistics data for the category of Computer Programmers. In 2022, the median pay in that role was $97,800.
Architects aren’t getting paid at a just average rate, though. As expert and experienced devs in a competitive niche, they are more likely to be in the top ten percent of that category.
But here’s the catch – so are any developers with AI expertise. BLS doesn’t yet separate out specific AI jobs from the group. Nor are there specific AI industries to look at just yet.
So the best you can say about AI architect salaries is that they are well above the top ten percent for programmers, which came in at $159,740 or more in 2022. You can expect the number to vary with location and industry, of course, as with all jobs. More information is available on our AI Salary page.
What Are the Best College Degrees for AI Architects?
There aren’t any college degrees out there for AI architecture. But many of the core skills you will rely on can be found in degrees in AI, machine learning, and computer science.
Because AI architect jobs most commonly go to the most knowledgeable senior devs, a graduate degree in those fields is preferred. A Master of Science in Computer Science with a concentration in Artificial Intelligence, a Master of Science in Machine Learning and Artificial Intelligence, or a Master of Science in Intelligent Systems Engineering are all good bets.
Many of the most senior developers and programmers who might be considering AI architect roles are long since out of the educational system, however. This is where educational certificates in AI can help make the grade.
These short programs, usually less than a year, assume a strong background in coding and mathematics. A program like an Advanced Certificate in Artificial Intelligence in Computer Science will build on that with laser-focused details in machine learning and AI paradigms and techniques. They are just the thing for experienced programmers who are transitioning to the AI environment… and potentially AI architecture jobs.
What Are Some AI Architect Courses to Consider?
What kind of coursework can AI architects pursue in regular AI educational programs to build their skills?
For starters, there are a few schools that offer specific courses in AI system architecture as part of their degree or certificate offerings. Some of these are even specific to certain AI technologies, like the Large Language Model (LLM) applications commonly used in Natural Language Processing.
Regular software architecture courses are more common, and a good fallback if nothing specific to AI is available.
AI architects will always benefit from big-picture programming work:
- System design
- User experience
- Hardware design
Due to their greater need to coordinate with other stakeholders, AI architects should also lean in to more communications and business-oriented coursework. Anything that improves your overall understanding of software uses and systems in a larger context will build your AI architectural skills.
Keep an Eye Open for AI Architect Certification Options
Anyone who has been around the software industry a while already knows the role that professional certification fills. Different from educational certificates, professional certs are offered primarily by industry groups or vendors.
They may have some teaching component, but the primary goal is to validate your skillset in the area they cover. This is usually accomplished through testing and an assessment of your on-the-job experience and educational background.
There are very few professional certifications currently available for AI architecture, although more are likely on the way. The Cloud AI Architect Certification, from Arcitura, is one very specific example, exploring your skills in AI-specific cloud architectural models and design patterns.
But that doesn’t mean you can’t find other certs to boost your job prospects.
In addition to the general AI certifications available today, a certification in software architecture can be a good choice to show off your qualifications.
Among industry professional groups, the iSAQB® (International Software Architecture Qualification Board) offers the CPSA®, Certified Professional for Software Architecture. It requires 3-4 days of training and passing a multiple-choice test to earn the foundational level, and additional training and a longer test to be certified at the advanced level.
For vendor certifications, you can look for offerings like the AWS Certified Solutions Architect-Professional. It requires passing a 75-question exam that validates your expertise specifically in building cloud-based solutions on AWS, a platform that is commonly used in AI training.
All of this is about forging new ground in the development world. You may be building a kind of expertise that no one has yet defined. As one of the architects of the most important new technologies the world has ever seen, you will be laying the cornerstones of an entirely new era for humanity.
2022 US Bureau of Labor Statistics salary and employment figures for Computer Programmers reflect national data, not school-specific information. Conditions in your area may vary. Data accessed December 2023.