I predicted that cloud providers would see a rise in demand for their services in 2024, given the push to use generative AI and the amount of resources (and money) this technology takes to operate. Now mainstream publications are also making this call, and we can all agree that generative AI will grow, and thus cloud computing will too. Simple math.
Like any change in a market, some will take advantage of the new opportunities, and some will be left behind. Recently, I’ve been getting many questions about what the workforce supporting cloud-powered generative AI will look like. More importantly, how can you take personal advantage?
Let’s explore some new roles that will likely emerge and how you can position yourself to serve in them.
AI cloud architect
Professionals specializing in designing and optimizing cloud architectures to support generative AI workloads will be in huge demand. How do I know? We don’t have enough cloud architects as is, and the mistakes occurring because of the lack of knowledge are starting to take their toll.
Companies will need trained, experienced cloud architects who understand how AI systems work and play well with existing cloud-based systems. If you’re interested, you’ll need training on how a cloud operates and the specific techniques that generative AI services use, such as data, knowledge models, APIs, and other forms of integration, plus how to ensure the scalability, security, and performance of AI systems.
AI data engineer
AI and data experts manage and preprocess large data sets used to train generative AI models. Most people understand that AI systems depend on high-quality, accurate data. AI data engineers ensure data quality, implement pipelines, and optimize data storage and retrieval. Their focus is more on data operations, but understanding how AI systems work, including training data, is essential.
This position will require an excellent working knowledge of databases, data integration, and how AI systems ingest data for training. This role also needs to understand data curation, quality, security, and governance. I suspect that most AI data engineers will come from the data operations side of things, not the AI side.
AI model curator
These individuals curate and select the most relevant and effective generative AI models for specific applications. They need to deeply understand the AI landscape and stay updated on the latest advancements, including the most helpful third-party tools and how models can be streamlined.
Again, this is more focused on operations. However, it requires specialized operations skills that most current ops team members won’t have. These people will likely come from the data ops side, but deep AI experience is essential.
Yes, this is a thing. With generative AI’s potential ethical implications, AI ethicists are crucial in ensuring responsible AI usage. Duties will include assessing and mitigating biases, privacy concerns, and potential societal impacts of these new generative AI systems in the cloud.
This position could come from many different areas. They could be primarily nontechnical roles. I suspect that many will have a business ethics background, but understanding technology will be a vital component of this role, even if that is not understood now.
Not to be confused with those who train people about AI, these professionals specialize in fine-tuning and optimizing generative AI models. Specifically, they work with data scientists and domain experts to prepare models for specific tasks and improve their performance and accuracy.
AI business strategist
Think AI-focused CTO or professional who can bridge the gap between technical AI capabilities and business goals. Their role will be identifying opportunities for generative AI deployment, developing strategies, and managing AI projects to drive business outcomes.
Most of these people will come from IT leadership roles with some technical background. They may have been project leaders or worked for the CIO at some point. They will need an eclectic mix of skills to be successful.
I suspect that I’m missing a few other roles that will be important, but they will likely be derivatives of the ones listed here. If any of these would be a good career move, then set up your training to head in that direction. Also, position yourself with existing or new jobs so you can move into these roles when they become available. Given that demand will outpace supply, these jobs will pay well, at least for the first few years.
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