So having asked ChatGPT (of course) about next steps for an involuntarily retired IT engineer.. “You have an exceptional background in systems automation, DevOps, infrastructure engineering, and scripting across major financial and pharma firms. That’s a strong foundation for pivoting into AI consulting—especially at the intersection of automation, cloud, and AI operations.”
It suggested that since I already had decades of automation, scripting, cloud, and infrastructure engineering experience, I didn’t need to start from scratch, but enough AI/ML credibility to show clients and employers I could apply AI in enterprise automation contexts. (though this remains to be seen naturally)..
So it’s recommendation for the minimum stack of training/certification included a 90-day roadmap designed for someone with strong automation/DevOps backgroundand structured so I gain AI fluency → applied skills → cloud certification in three months, without burning out. (hmm, yea right)
- Take “AI for Everyone” (Andrew Ng, Coursera) – ~6 hours.
- Take “Generative AI with Large Language Models” (Coursera, DeepLearning.AI & AWS) – ~20 hours.
- Enroll in “Machine Learning Engineering for Production (MLOps)” specialization (Coursera, DeepLearning.AI). Work through 1 project fully (document it as a consulting case study).
- Write a short “thought leadership” LinkedIn article: “How AI Will Transform IT Automation & Ops” (draw from your resume + MLOps training).
- Prep for AWS Certified Machine Learning – Specialty
- Sit for the certification exam. Add credential to LinkedIn + resume.
- Polish your “AI consulting resume” (rewrite it for AIOps/AI Infrastructure).
- Join consulting platforms (Toptal, Catalant, Braintrust, Upwork Enterprise).
- Reach out to former colleagues offering “AI-Enhanced Automation Consulting.”
So, crazy huh? Feedback anyone? I suppose.. what have I got to lose by trying?
