The Evolving Need for AI Engineering and GenAI Adoption Consulting
The tools are here but the educational gap presents an opportunity
What started as my annual tech stack review has evolved into something bigger: recognizing that AI Engineering isn't just a buzzword. It's a critical need that most organizations haven't figured out yet.
Amazon's new Bedrock AgentCore platform announced today highlights exactly why this matters. While Big Tech can build powerful AI agent platforms, there's a massive gap between having the technology and actually using it effectively. As this article by Rachyl Jones, a Tech Fellow at Semaphor, puts it:
The argument from Big Tech executives is that the technology will make workers’ lives easier, so why wouldn’t they adopt it? That may be true, but it also requires every employee, including the tech-challenged and tech pessimists, to experiment with agents enough to reach their personal aha moment. Education could fill the gap — imagine training videos or workshops hyper-specific to automating personal workflows — but that’s not Amazon’s job, and many businesses lack the time and bandwidth to create programming.
This is where AI Engineering and adoption consulting looks to me to be becoming and essential practice. Organizations need more than just access to AI tools. They need stewardship, education, and practical guidance on integrating these technologies without disrupting what already works.
After 30 years in mobile/web/cloud development, I'm finding this intersection of technical expertise and organizational change management aligns perfectly with my own growing interest in helping teams bridge the gap between AI potential and AI reality.
The tools exist. The education and implementation strategy? That's the real opportunity.
Evolving as a Software Engineer
The immediate challenge is packaging my skills and passion for building dynamic, sustainable, fact-based systems (fundamental in GenAI) in a way that clearly demonstrates where I can help organizations navigate AI adoption. I can't be the only software engineer evolving alongside the industry while waiting for these new types of roles to crystallize within organizations.
AI Engineering and GenAI Adoption Consulting is the direction I'm defining for myself, even though job boards don't yet reflect what I believe organizations actually need quite yet. "AI Engineer" positions are appearing more frequently, but they typically have requirements like "3+ years delivering generative AI applications" and focus on technical delivery rather than the educational and organizational change management that most companies desperately need. I believe the change management and implementation are two sides of the same coin. You can’t split them in my opinion.
The gap is clear: organizations have access to powerful AI tools but lack the expertise to implement them effectively without disrupting existing workflows. That's where the real opportunity lies.
It's a wild time to be job hunting, but I'm seeing a definitive rise in opportunities that align with what I want to build. The demand is there, even if the job descriptions haven't caught up yet.
That's actually the best news.