How AI Is Changing What It Means to Be an Engineer
Interview with Daniel Wellner, Director Platform Engineering, Security and DevOps at Averity
By Chris Allaire — November 3, 2025
In today’s technology landscape, the traditional boundaries between engineering roles are dissolving.
Once, DevOps, Data Engineering, and Software Engineering were distinct lanes. Now, those roads converge into something far more complex — and far more in demand.
That’s where Danny Wellner lives.
Danny has spent nearly a decade recruiting some of the most advanced engineers in infrastructure, DevOps, and platform engineering. Trained by Averity co-founder Alex Dubovoy — widely regarded as one of the godfathers of DevOps recruiting — Danny has become one of the most trusted specialists in the field, helping companies build the technical backbone behind AI and next-generation systems.
“Pretty much every single technical role now has some sort of AI play or understanding built into it,” says Wellner. “It’s no longer just about deployment speed — it’s about building the ground for agentic-based systems and AI-driven services.”
The Age of the Cross-Functional Engineer
What skills do AI-era engineers need most?
Traditional job boundaries are vanishing.
“You used to have a software engineer who built code, a data engineer who managed ETLs, and an infrastructure engineer who deployed systems,” Danny explains. “Now, companies want someone who can do all three — and understands AI tools on top of it.”
With nearly a decade of experience recruiting elite DevOps, platform, and infrastructure engineers, Danny brings deep technical fluency and a vast network of senior-level talent. Having witnessed how DevOps evolved into Platform Engineering and now into AI-driven infrastructure, he’s been at the center of that transformation since day one.
The DIY AI Era: How Top Engineers Are Upskilling
Where are the best AI engineers coming from?
If you think companies are training their people for this — think again.
“A lot of companies aren’t running this stuff in production yet,” Danny notes. “So the people who really know it? They’re learning on their own time — taking courses, experimenting, building projects, or working at the few companies actually pushing this tech forward.”
That curiosity and self-driven learning are the differentiators. Engineers who tinker are the ones who thrive.
Recruiters like Danny stay close to the action — tracking which companies are truly running AI in production and maintaining deep personal relationships across the industry.
“It’s not hard to keep up with people,” Danny says. “It’s just time-consuming. Maybe only 10% are working on cutting-edge AI, but those relationships are gold.”
Security, Data, and the New AI Vulnerabilities
How is AI impacting cybersecurity and data governance?
Every innovation creates new exposure. In 2025, security has never been more volatile.
“The attacks have ramped up tenfold,” says Danny. “It’s not just ransomware — it’s the sheer volume of attempts coming from everywhere.”
As companies race to integrate AI, new risks surface — from data leaks to unintentional public disclosures via tools like ChatGPT.
“You upload a public document to an AI tool, and it’s now public information,” Danny warns. “One small mistake can leave your entire company vulnerable.”
That’s why AI security and data governance have become core pillars of modern engineering. The rise of Application Security Engineers — software-savvy security experts who understand vulnerabilities in code and architecture — is reshaping what it means to protect a business.
“Data is the most valuable resource in the world right now,” Danny says. “Protecting it and keeping it clean — that’s the real challenge.”
What Top AI Engineers Earn in 2025
How much do AI engineers make today?
Averity’s world lives at the top of the talent pyramid. Senior, Principal, and Staff-level engineers aren’t cheap — and they shouldn’t be.
“Baseline, you’re looking at $180K to $190K,” Danny shares. “But total comp can range up to $400K–$500K, depending on experience and specialization.”
And yes — the unicorns exist. Some engineers in AI and platform architecture are commanding $800K to $1M+ total compensation packages.
“The top-round draft picks get paid,” Danny says. “If you want to compete with the best companies in the world, you’ve got to pay top-round draft-pick salaries.”
Why Human Connection Still Wins in Recruiting
Even in the age of automation, the human touch still separates the good from the great.
Danny emphasizes that relationships remain the currency of elite recruiting.
“Relationships are still everything,” he says. “Keeping the old ones healthy and building new ones — that’s where the magic happens.”
Few recruiters understand the evolution of infrastructure roles like Danny Wellner. After nearly ten years in DevOps and platform recruiting Danny’s perspective bridges the past, present, and future of how engineers build the systems that power AI.
And that’s where firms like Averity stand out — blending deep technical specialization with genuine human connection.
In a world where AI writes job posts and scans résumés, Danny and his team are talking to the people building the future — one connection at a time.
Key Takeaways
- AI is no longer a role — it’s a requirement. Every engineering discipline now integrates AI tools and systems.
- Platform Engineers are the new rockstars. They merge DevOps, software engineering, and AI infrastructure.
- Security threats have exploded. AI introduces new vulnerabilities, making data governance critical.
- The talent gap is real. Only ~10% of engineers are working on cutting-edge AI systems.
- Top talent costs top dollar. Senior AI engineers earn $300K–$500K+, with some reaching seven figures.
- Relationships drive results. Human connection — not automation — remains the foundation of great recruiting.
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