As business leaders rush to tap into the power of artificial intelligence, hiring AI developers who can turn complex algorithms into real-world solutions is key to staying ahead. But with demand soaring, finding the right talent is tougher than ever.
The shortage of AI skills is projected to take a large toll on businesses. Research from the International Data Corporation predicts that, by 2026, 90% of businesses will have felt the impact of the skills shortage — to the tune of some $5.5 trillion in lost revenue.
Organizations are going to have to find smart ways to hire artificial intelligence developers to keep projects moving forward.
Let’s walk through what it takes to hire the AI developers you need. We’ll cover the key skills you need in AI developers, explore different hiring models, and offer tips for optimizing the hiring process to find the right talent for the role.
Why It’s Hard to Hire AI Developers
AI developers are among the most difficult jobs for companies to fill right now. From fierce competition for talent to a dwindling pipeline, here are some of hurdles you’ll need to overcome to hire the right people for the job.
High Demand for AI Skills
The demand for AI skills is skyrocketing as AI revolutionizes industries across the board — from healthcare and finance to retail and manufacturing. Companies are eager to tap into AI’s potential to boost efficiency, make smarter decisions, enhance customer experiences, and drive innovation. As businesses race to stay ahead of the competition, the need for talented AI developers who can build, implement, and maintain these cutting-edge technologies is only increasing.
Insufficient Supply of Skilled Professionals
AI is a complex and rapidly evolving field that requires a deep understanding of both theory and practice. Learning AI involves mastering challenging subjects like machine learning, neural networks, data science, and programming — each with its own steep learning curve. Plus, as AI technology advances, even experienced developers need to keep their skills up-to-date, making it hard for the supply of qualified professionals to keep pace with the growing demand.
Educational and Training Gaps
Traditional education systems haven’t fully caught up with the fast-moving AI industry. Many computer science programs still focus on broad foundational topics, with limited opportunities to specialize in AI and machine learning. Since AI draws on a mix of disciplines — like math, statistics, and data science — many educational programs can’t offer the comprehensive training needed to fully prepare students.
Additionally, the hands-on experience crucial for mastering AI tools often goes beyond what’s typically provided in the classroom, leaving a gap between academic learning and the real-world skills employers need.
10 Key Skills to Look for in AI Developers
Top AI developers know how to blend their expertise in programming, machine learning, and collaboration (among other skills) to create cutting-edge AI solutions that solve real-world problems and open up exciting new opportunities.
When you hire AI engineers with these key skills, you’re not just adding talent to your team — you’re fueling your company’s innovation and growth.
AI and Machine Learning Frameworks
Modern developers must be well-versed in AI and machine learning frameworks such as Python, TensorFlow, Keras, PyTorch, Scikit-learn, and R. Mastery of these tools is crucial for the effective construction, training, and optimization of AI models.
Data Science
Data science skills are indispensable for developers, particularly those working in AI. Proficiency in statistics, predictive modeling, and data visualization enables developers to derive actionable insights from vast datasets. Familiarity with tools like Snowflake, Databricks, dbt, Tableau, Power BI, Redshift, and Spark is essential for analyzing and visualizing data, which is foundational in informing AI model development and ensuring that solutions are both effective and relevant.
Programming Languages
Knowledge of programming languages such as Python, Java, C++, and R is fundamental for AI developers. These languages provide the necessary tools to implement algorithms and construct robust AI systems efficiently. A strong grasp of programming enables developers to translate theoretical models into practical applications, ensuring the development of reliable and scalable AI solutions.
Large Language Models (LLM) and Natural Language Processing (NLP)
In an era when digital interactions are increasingly prevalent, proficiency in NLP and understanding of LLMs are critical. These skills allow developers to enhance user interfaces with conversational AI, making digital interactions more intuitive and user-friendly. This expertise is crucial for designing systems that seamlessly interpret and respond to human language, improving user engagement and satisfaction.
System Administration and DevOps
For AI developers, expertise in system administration and DevOps is essential. Skills in using tools like Jenkins, Kubernetes, Docker, Terraform, and CI/CD pipelines enable the efficient deployment and maintenance of AI models across various environments. This ensures that AI applications are reliable, scalable, and continuously integrated into existing systems without disruption.
SDET and Quality Assurance
Quality assurance and software development engineering in test (SDET) are critical for ensuring that AI models and systems operate flawlessly and meet predefined quality standards. Knowledge of testing tools like Selenium, Cypress, Jest, and TestNG is crucial for developers to validate the functionality and performance of AI solutions, ensuring they deliver the intended outcomes without errors.
Database Management
Effective database management is a cornerstone of AI development. Developers must be proficient in handling databases using technologies like MySQL, PostgreSQL, MongoDB, and Redis. Knowledge of efficient management and retrieval of data is vital for training and operating AI models, ultimately enhancing performance and scalability.
Cloud Platforms
Experience with cloud platforms such as AWS, Azure, and GCP is important for AI developers. These platforms offer the infrastructure necessary to deploy and scale AI solutions efficiently, providing flexibility and high-performance computing power that can significantly accelerate the development and deployment of AI technologies.
Cross-Disciplinary Collaboration
Collaboration across different disciplines is vital for the success of AI projects. It ensures that AI solutions are well-aligned with business objectives and user needs. This skill is crucial for developers to integrate diverse perspectives into their work, enhancing the relevance and impact of AI technologies.
Effective Communication
The ability to communicate complex AI concepts clearly to both technical and non-technical stakeholders is crucial. Effective communication ensures that all parties involved in a project are well-informed about goals and progress, facilitating smoother implementation and adoption of AI solutions.
3 Models for Hiring AI Developers
You have options for incorporating AI developers into your workforce beyond traditional full-time hiring. Whether you hire a developer full-time, work with contractors as needed, or bring in teams of specialists on a project-by-project basis, you have options for meeting your specific talent demands.
Full-Time Staff
Bringing AI developers on board as full-time staff means you have a dedicated team that’s deeply integrated into your company’s culture and mission. They’re aligned with your long-term goals and can provide continuous development and maintenance of AI projects. For example, hiring generative AI engineers full-time can be instrumental in developing and maintaining an in-house AI system that evolves with your business needs over time.
However, this approach can be expensive, considering the costs of salaries, benefits, and ongoing training. Plus, in a competitive market where top AI talent is highly sought after, finding and keeping the right people can be tough. You might find that you’re competing with tech giants like Google or OpenAI for the same skilled professionals.
You can partner with universities, colleges, certification programs, bootcamps, and online academies to source AI developers. You can use these partnerships to identify and build a pipeline of promising candidates who are passionate about AI and eager to put it to practical use.
You can also source AI developers through specialized online communities like GitHub, Kaggle, and AI Stack Exchange.
Independent Contractors
Independent contractors give you the flexibility to bring in expert talent on a project-by-project basis. This means you can scale your team up or down depending on your needs, which can be more cost-effective than maintaining a full-time team. For example, you might hire a generative AI developer to work on a specific AI feature for a product launch without committing to a long-term employment contract.
On the flip side, contractors might not have the same level of investment in your company’s success or understanding of your culture and processes. This can sometimes lead to challenges in communication and coordination, especially if they’re working remotely. For instance, a contractor might complete a project and move on, leaving your in-house team to handle any unforeseen issues.
On-Demand Teams of Engineers
On-demand teams offer access to a broad range of specialized skills and expertise, which can be a game-changer for tackling complex or highly specialized AI projects. This model allows you to quickly assemble a team with the precise skills needed for a particular task. For example, if you’re developing a new generative AI solutions product that requires expertise in natural language processing, an on-demand team can bring in just the right experts.
That said, managing an on-demand team can be tricky. Clear communication and strong project management are essential to keep everyone aligned with your company’s goals. Additionally, there may be concerns about consistency and continuity if the team isn’t available for future projects. For instance, you might struggle to maintain the same level of quality and understanding if a new team needs to be brought up to speed later on. Look for IT staffing solutions providers who curate the right talent to meet your one-of-a-kind culture and fit right into your workflow.
How to Level Up Your AI Developer Hiring Process
Bringing in top AI talent is key to pushing your company’s innovation forward. Walk through how to attract, interview, and onboard AI developers so you can find the right people and help them thrive in your organization. With the right approach, you'll build a team that's ready to take your AI projects to the next level.
Promote Your Employer Brand
Attracting top AI talent starts with showing that your company is the place where skilled developers can thrive. To bring in the best, emphasize what makes your brand uniquely appealing, such as your commitment to innovation, professional growth, or a supportive work environment.
In a tough skills market, offering a strong compensation package is key. Competitive salaries, equity options, and comprehensive benefits send a clear message that you value their expertise and are invested in their long-term success. Promote pay, benefits, and other rewards such as continuous learning or potential for mobility.
Assess for Skills and Growth Potential
Assessments, test projects, and interviews give you an opportunity to see what the promising candidates are capable of — and where they may want to take their careers in the future.
Assess their proficiency in programming languages and AI frameworks, as well as their understanding of machine learning, to gauge their technical capabilities for handling your AI projects. Present real-world AI scenarios to evaluate their critical thinking, problem-solving skills, and ability to navigate complex challenges.
Evaluate applicants’ ability to communicate complex AI concepts clearly to non-technical team members and ensure their written documentation is thorough and accessible. Determine their commitment to continuous learning by asking about recent efforts to stay current with the latest AI developments. Consider their alignment with your team’s values, work style, and passion for AI to ensure they are a good cultural fit for your company.
Onboard New AI Developers Up for Success
Once you’ve found the right AI developers, you need an effective onboarding program for seamlessly integrating them into your culture and workflows.
Start by setting clear expectations around their roles, responsibilities, and how their work ties into broader project goals. This helps them understand where they fit in and how they can contribute right from the start.
Make sure they have access to everything they need, from comprehensive documentation to the latest tools and technologies. Providing the right resources upfront ensures they can quickly get up to speed and start making an impact.
Keep Moving Forward With X-Team’s AI Talent Solutions
The speed of business is only increasing, while hiring is getting slower. You need the help of an experienced AI talent partner like X-Team that’s ready to help you fill the gaps and capitalize on business opportunities.
When you partner with X-Team, you get a partner that will match you with highly skilled staff who easily integrate into your workflows and culture — delivering results from day one. You can focus on building your product — not sitting in interviews or scrambling to replace people. We’ll help you hire the talent you need to deliver your most ambitious projects on time and under budget.
Find out how X-Team can meet your on-demand engineering needs.
