I want to tell you something that nobody in the hiring industry will say, because their entire business model depends on you not knowing it.
The reason you can't find great AI engineers isn't that they don't exist. India alone produces 1.5 million engineering graduates every year. There are engineers right now — at VIT, Manipal, triple-IITs, at colleges you've never heard of — who are building production AI systems in their spare time that would impress the teams at Anthropic and OpenAI.
The reason you can't find them is that someone inside your company is making sure you don't.
"94% of business leaders in the US report significant difficulties filling AI roles. Not because the talent doesn't exist. Because the people doing the hiring can't recognize it when they see it — and some of them are incentivized not to."
— ManpowerGroup Global Talent Shortage Report, 2026
1. The Middle Manager Problem Nobody Talks About
There is a class of people inside every major company — and inside most startups that have scaled past 20 people — who got hired because they interview brilliantly. They have the right credentials. The right logos on their LinkedIn. The right vocabulary. They can present beautifully, write compelling reports, and make any situation sound like it's under control.
They are, in the truest sense of the word, professional employees. They have optimized their entire career for the act of getting and keeping a job. And they are extraordinarily good at it.
But here is what they are not good at: building things. Shipping things. Making hard technical decisions under pressure. Evaluating engineers who are better than they are. And this is where the problem starts.
Because once these people are inside your company, they do one thing above everything else: they protect their position by controlling who gets through the door.
They block founders from getting hired because founders make them look unnecessary. A founder who's shipped a real product, managed a team, and made decisions with incomplete information will immediately expose the gap between what the middle manager claims to do and what they actually do. So the founder gets filtered out. "Not a culture fit." "Too independent." "Wouldn't work well in a structured environment."
They block raw talent because raw talent is harder to manage — and harder to take credit for. An engineer from a tier-2 college who can build a production RAG pipeline in a week is a threat to a manager who needs to look like the smartest person in the room. So the engineer gets filtered out. "Doesn't have the right background." "We need someone more senior." "The resume doesn't match what we're looking for."
Average reported loss: $17,000. For senior AI engineers, the real cost is $400K–$600K when you count lost runway, team drag, and missed product milestones.
The cost of a bad hire isn't just the salary. It's the six months of runway you burned waiting for them to ramp up and deliver — and the team morale damage when they didn't.
And they present curated information upward. The CEO sees dashboards that look fine. The reports say the team is performing. The roadmap is "on track." What the CEO doesn't see is the engineer who could have shipped the AI feature in two weeks who never made it past the first screening call. What the CEO doesn't see is the founder-turned-engineer who applied three times and got rejected each time by a recruiter who didn't know what a RAG pipeline was.
The CEO thinks things are going well. The manager is comfortable. And the company is quietly falling behind — because the people who could actually build the future never got through the door.
2. Taking Credit for YouTube's Growth
I want to give you a mental model for what's happening, because I think it explains the problem better than any statistic.
Imagine it's 2012. YouTube's recommendation algorithm is just starting to work. Watch time is exploding. Every metric is going up and to the right. The VP of Growth at YouTube is presenting to the board. He's showing incredible numbers. He's taking credit for the growth. And in a narrow sense, he's not wrong — he was there, he ran the team, he approved the strategies.
But here's the truth: anybody could have grown YouTube in 2012. The algorithm was working. The product was right. The market was ready. The growth was going to happen regardless of who was in that VP seat. The question isn't whether he grew YouTube. The question is: what happens when the tailwind stops? What happens when the algorithm needs to be rebuilt from scratch? What happens when you actually need someone who can build?
That's the moment when you find out whether you hired a builder or a presenter. And by then, it's usually too late — because the builder you needed was filtered out three years ago by the presenter who's now your VP.
"I hired an IIT graduate who spent his first month trying to manage my best programmers instead of writing code. He had the pedigree, the confidence, the vocabulary. He could present beautifully. But he couldn't build. And worse — he was actively slowing down the people who could."
— Ajay Jetty, Founder, Jetty Forge
This is not an isolated story. It's a pattern. And it's playing out right now at companies that think they're building AI capabilities but are actually building a layer of management that will eventually prevent them from building anything at all.
3. The Founder Who Can't Get Hired
Now let me tell you about the other side of this problem — the one that's personal to me, and personal to thousands of people who've built real things and then tried to re-enter the job market.
Think about what it means to have been a founder. You've made decisions with incomplete information, under real pressure, with real consequences. You've shipped products to real users. You've managed engineers, designers, and PMs. You've dealt with investors, customers, and competitors simultaneously. You've learned more in two years of building than most corporate employees learn in a decade.
You are, objectively, one of the most capable people in the job market. You have the skills. You have the proof. You have the scars.
And when you try to get hired at a top company, the corporate recruiter sees "Founder" on your resume and thinks: too independent, won't follow process, not a team player, will leave as soon as they have another idea.
A Fortune study published in 2024 confirmed what every ex-founder already knows: corporate recruiters have a documented, measurable bias against ex-entrepreneurs. They get stereotyped as people who don't want to "be a small piece of the puzzle." The study found that even when founders had directly relevant experience, they were systematically passed over in favor of candidates with more conventional career paths.
"Most recruiters didn't know what to do with my 'founder' background. It felt like they saw it as indecisiveness or a lack of commitment — when really it was the most intense, high-stakes work I'd ever done."
— Reddit r/startups, 2024 (representative of hundreds of similar accounts)
Why does this happen? Because the recruiter — and the middle manager they're screening for — doesn't want someone who will make them look unnecessary. A founder who walks into a team and immediately starts building, questioning processes, and delivering results is a direct threat to the manager who's been coasting on the tailwind.
So the founder gets rejected. Not because they're not qualified. Because they're too qualified — and the wrong people are doing the filtering.
4. The Raw Jewels Nobody Is Looking For
Here's what I discovered after reviewing 15,000 engineering applications and training 40+ engineers on real production AI projects:
The best AI engineers in India are not at IITs.
I know that's a controversial statement. The conventional wisdom — the thing that every corporate recruiter and every hiring manager believes without question — is that IIT is the gold standard. And IIT produces excellent engineers. But "excellent" and "best" are not the same thing. And the filtering process that gets someone into IIT is not the same filtering process that identifies someone who can build production AI under real constraints.
The engineers I've found who are genuinely exceptional — the ones who made it through the Jetty Forge process, the ones who are now building production AI that companies 10x their size can't replicate — are from VIT, Manipal, triple-IITs, and colleges you've never heard of. They're raw. They're hungry. They've been building things in their spare time not because someone told them to, but because they can't stop.
But they don't have the right pedigree. They don't know the right people. They get filtered out before a human ever reads their name — because the algorithm is looking for keywords, not capability. Because the recruiter is looking for logos, not proof. Because the middle manager is looking for someone who went to the same school they went to, not someone who can actually do the job.
Applications reviewed by the Jetty Forge founder
Engineers trained on real production AI projects
Who made it through all five stages of The Forge
I gave these engineers real tools. Real problems. Real constraints — LLM cost optimization, context and memory architecture, data pipelines that have to handle production load, cloud infrastructure that has to be cost-efficient at scale. I threw them in the deep end and watched what happened.
Some of them built things that would impress engineers at Anthropic. Not in theory. In production. With real users. And they did it faster, and cheaper, and with more creativity than engineers I've seen at companies spending 10x more on their AI stack.
Those are the engineers in the Jetty Forge network. Not the ones with the best resumes. The ones with the best proof.
5. What Happens to Your Company If You Keep Hiring This Way
Let me be direct about what's at stake, because I think most CEOs and CTOs are not fully reckoning with the consequences.
The AI transition is not a gradual shift. It's a discontinuity. The companies that build real AI capabilities in the next 24 months will have structural advantages that will be nearly impossible to overcome. The companies that spend those 24 months running broken hiring processes, filtering out the best talent, and building layers of management that prevent builders from building — those companies will fall behind. And some of them will disappear.
Entry-level tech hiring has already plummeted 73%. Companies aren't hiring junior engineers anymore — they need production-ready AI builders. But here's the contradiction: the companies demanding production-ready AI builders are running hiring processes that select for people who are good at being hired, not people who are good at building. They want builders. But their process — controlled by the middle managers who benefit from the status quo — delivers presenters.
The cost of this failure is not abstract. A bad senior AI hire costs between $400,000 and $600,000 when you count salary, benefits, recruiting fees, onboarding time, team drag, and the opportunity cost of the work that didn't get done. And that's just the direct cost. The indirect cost — the product that didn't ship, the competitor that pulled ahead, the engineers who left because they were frustrated working under someone who couldn't evaluate their work — is much larger.
"You get mediocre results. You blame the technology. You hire a consultant to tell you what went wrong. And quietly, your competitors — the ones who found a way to access real talent — pull further ahead. Eventually, your company disappears. Not because the market wasn't there. Because the people who could have built for it never got through your door."
6. Independence Through Jetty Forge
By building Jetty Forge, we are creating an ecosystem where their pedigree gatekeeping doesn't matter.
This is a platform for the 0.1% who are often "too smart" or "too founder-minded" for the corporate machine. Engineers who've been overlooked because they went to the wrong school. Founders who've been filtered out because their resume says "Founder" instead of "Senior Engineer at Google." Product managers who understand AI deeply enough to build it, but can't get past the first round of interviews because they don't have the right logo on their LinkedIn.
Jetty Forge makes us the gatekeeper. Not the HR managers who've never shipped anything. Not the recruiters who are optimizing for keywords. Not the middle managers who are protecting their own position by keeping the best talent out of reach.
Us. The people who've actually done the work. Who know what production AI looks like. Who can tell the difference between someone who's used ChatGPT and someone who's built a production RAG pipeline that handles real load with real cost constraints.
And for the talent in our network: we don't just place you. We negotiate for you. We know what you're worth — because we've seen you build. We know what the market is paying. And we will fight for the best deal you've ever seen, because your work deserves it and because the companies we work with understand that paying for the top 0.1% is the best investment they will ever make.
Instead of worrying about whether the corporate machine will accept you, you are now part of a marketplace that Google, Anthropic, top YC startups, and other elite companies will eventually have to come to — if they want real builders.
"The engineers who will define the next decade of AI are not going to be found on LinkedIn. They're not going to apply to your job posting. They're not going to pass your recruiter screen. They're in our network. And if you want them, you're going to have to come to us."
7. What Jetty Forge Actually Does
We don't find talent. We forge it. And then we place it directly — bypassing every gatekeeper between the CEO and the engineer who can actually do the job.
Every engineer in the Jetty Forge network has completed five stages that are harder than most companies' entire hiring loops:
AI Assignments
Real-world problem sets designed by the founder. Not LeetCode. Not toy problems. The exact challenges that production AI teams face — RAG architecture, prompt optimization, LLM cost reduction under real constraints. Most candidates don't make it past this stage.
Technical Interviews
Deep-dive sessions probing AI/ML fundamentals, system design for LLM applications, and the candidate's actual reasoning process. We want to see how they think, not what they've rehearsed.
Live Coding
Unscripted, observed problem solving under pressure. We watch how they think, how they debug, how they communicate. The best engineers are calm, methodical, and creative when the stakes are real.
Culture Fit
Values, communication style, startup vs. enterprise alignment. How they handle ambiguity, feedback, and failure. This is where founder-minded engineers consistently outperform their corporate-trained counterparts.
Trial Project
A paid two-week engagement on a real project with real users. They deliver. They communicate. They prove they can do the job — before you commit to hiring them. No surprises. No ramp time. Just proof.
When a company comes to us — a CEO, a CTO, a YC founder — they don't browse a database. They don't post a job. They submit one request describing exactly what they need, and we come back to them with one to three hand-picked engineers who have already proven they can do it.
Full-time. Contract. Managed team. Whatever removes the most friction. The only thing we don't do is compromise on the quality of the talent — or let a middle manager anywhere near the process.
This Is the Problem I Was Born to Solve
I've spent years doing what no one else would do — scanning 15,000 applications, training 40+ engineers on real production AI, finding the raw jewels that every other company threw away. I've lived the founder bias firsthand. I've watched brilliant engineers get filtered out by people who couldn't evaluate their work. I've built real products with real users and felt what it's like to have that work dismissed because it didn't come with the right logo.
And I've built something that changes the equation. Not just for the companies that need real AI talent. For the engineers who have the skill and the proof but can't get past the gatekeepers. For the founders who've built something real and deserve to be recognized for it. For the CEOs who are ready to stop trusting the curated reports and start trusting the proof.
The middle managers had their era. It's over.
— Ajay Jetty, Founder, Jetty Forge