(Crazy AI art huh? I asked DALL-E3 to create an image of itself with my logo… insane)
The rapid advancement of AI technologies has sparked conversations about the evolution of tech jobs - More specifically if those in the tech industry are more prone to losing their jobs to AI - being replaced by artificial intelligence. Cybersecurity Analyst being replaced by AI who can detect and respond to threats much faster. Programmers being replaced by AI counterparts who can develop programs, API’s, and other automations. Contrary to fears of AI replacing human roles, I firmly believe AI is creating new opportunities and enhancing existing careers, especially in application development and infrastructure related roles.
Application Development related jobs
With the rise of AI-powered chatbots and voice assistants, prompt engineers are becoming critical assets. They craft conversational interfaces that effectively communicate with users, leveraging a deep understanding of natural language processing (NLP) and human-computer interaction. Programmers who have a strong understanding of user behavior can easily step into prompt engineering roles utilizing strong coding skills. These people help make AI interactions seamless and intuitive.
AI Interface designers are responsible for creating user-friendly experiences which connect to the backend LLM / AI models. Designing visualizations, dashboards and other interfaces which can clearly communicate AI insights and outputs ensures that AI/LLM tools are accessible and actionable for end-users.
RAG (Requirements, Analysis and Generation) Specialists analyze business requirements and generate technical specifications for AI system development, ensuring alighnment between business goals and technical execution. These people generally have strong analytical skills and excellent communicatino abilities with experience in project management tools.
Automation using AI driven scripts, bots, tools, frameworks (such as CrewAI), etc., which can perform repetitive tasks (data entry for example) can boost your career no matter which field you are in (programming/app dev, infrastructure, cybersecurity, etc.). This can free up human resources for more strategic and creative tasks leading to higher productivity towards an end goal. And Automation isn’t going to replace your job, AI (at the time of this writing) isn’t at the point where it can “learn” from it’s mistakes effectively (it’s getting there - EOY 2024 looks promising)
Infrastructure related jobs
AI isn’t just for application development related jobs - AI and LLM related jobs are found throughout the infrastructure side of the house as well. Cloud and computer management roles rely on someone who know and understand the requirements to run LLM’s. They optimize Cloud and On-Premise infrastructure resources, manage distributed computing environments, scaling, and ensure efficient data processing. These individuals need to dive deeping into cloud infrastructure with experience in kubernetes and strong problem-solving skills in order to understand how to scale AI/LLM operations and enable quick/reliable data processing.
Along with that, those in the Data Management field will be highly sought after as data is the CORE of LLM’s. Data managers will be crucial for designing and implementing data pipelines, warehousing and analytics platforms to support AI-driven decision-making. SQL/NoSQL databases, ETL tools and strong analytical skills play a huge role to ensure that data is accessible, clean and usuable for the models performance.
Those involved with Infrastructure as Code, automated infrastructure, etc., will need to know how to scale up and out with regards to LLM’s, and can actually use LLM’s to assist with the scaling. Furthermore, familiarity/expertise in Docker/Kubernetes, CI/CD Pipelines, and monitoring tools and how to use these with LLM’s will be necessary.
Cybersecurity (which can really be an Application or Infrastructure related role) specialists (broad term here) need to know how AI/LLM impacts their applications and security involved. AI security engineers are proficient in machine learning, and SIEM systems which will enhance an organization’s ability to detect and respond to cyber threats swiftly, reducing the risk of data breaches and cyber attacks. Threat Intelligence Analysts will probably use AI and LLM’s the most, being able to gather, analyze, and interpret the data much quicker to fortify their information systems. Proficiency with AI-driven threat intelligence platforms will be important with these personnel. Probably my favorite cybersecurity role, one I want to explore more into, would be Automated Incident Responders who can leverage AI/LLM to automate detection and response to cybersecurity incidents. Developing workflows and playbooks, using AI Agents, AI Automation, incident response procedures and programming skills to develop automated scripts and responses to reduce response/mitigation time. A counterpart to this though is the threat of AI being used as an offense to businesses, so equally as important is understanding how to defend against automated AI attacks.
Using AI and LLM in Tech Jobs
Developing Domain Expertise/deeper understanding of a specific industry can be easily obtained using LLM’s. Hosting your own LLM to scour through your own notes, PDF’s, or data can prove beneficial to recall what you may have written down years ago while studying for a specific topic, or using LLM’s to dive deeper into a topic you didn’t understand. Do note that LLM’s are not the know-all/end-all solution and to always cross check references when unsure (read: hallucinations and biases). This can lead to understanding how LLM’s can be used for business purposes (internal Wiki, either replacement or addition to for example).
In conclusion, AI and LLM technology is not eradicating jobs; it’s reshaping and enhancing them. By understanding and adapting to these new tools, and understanding how you can use these tools in current roles (such as roles in application development or infrastructure), tech professionals can not only stay relevant but thrive in an AI-augmented future. Embrace the change, learn continuously, and don’t get left behind in what appears to be the fastest evolution of technology we have seen since the Dot Com boom…