In a tech landscape where talent is abundant but often overlooked, especially within immigrant communities, one company is using artificial intelligence to level the playing field. I’m Kaila Davis, and today I’m speaking with Dominic Jainy, an IT and AI expert from NextTechJobs. His platform is making waves by automating the grueling job search process for tech professionals, turning months of frustration into tangible career growth. We’ll explore how their AI-driven tools are dismantling systemic barriers, from bypassing automated resume screeners to tapping into the unlisted “hidden job market.” We’ll also discuss the platform’s impressive success in helping users secure significant salary increases and dramatically reduce their job search time, and get a glimpse into the future of AI in career development.
Your AI Resume Multiplier generates multiple resume versions optimized for ATS. Can you walk me through how this tool goes beyond simple keyword matching to tailor a candidate’s experience for different roles, and what specific elements it adjusts to get past advanced screening systems?
Absolutely. It’s a common misconception that beating an Applicant Tracking System, or ATS, is just about keyword density. Modern systems are far more sophisticated, and that’s where our AI Resume Multiplier truly shines. It doesn’t just stuff in keywords; it performs a deep contextual analysis of the job description. It identifies not just the what—the skills—but the how—the implied seniority, the project scope, and even the company’s cultural language. The tool then intelligently rephrases a candidate’s experience, adjusting bullet points to highlight the most relevant achievements for that specific role. It also perfects the formatting—fonts, margins, date formats—which are invisible hurdles that can get a perfectly qualified candidate rejected before a human ever sees their name. It’s about creating a holistic, compelling narrative that the machine understands and a hiring manager appreciates.
The platform specifically aims to help immigrant tech professionals who face hurdles like underemployment and cultural barriers. Beyond automating applications, what specific strategies or features help a candidate overcome these nuanced biases, and could you share an example of how this has made a tangible difference?
This is really the heart of our mission. The founder is an immigrant himself, so that experience is baked into our DNA. Automation is the engine, but cultural translation is the navigation system. One of the biggest challenges is that immigrant professionals often downplay their accomplishments, which doesn’t resonate in the North American market. Our platform provides a supportive community and mentorship to address this directly. We guide users on how to frame their international experience as a global asset, not a liability. For instance, we had a senior developer from overseas who was consistently getting offers for junior roles. Our system helped him rephrase his project management experience using industry-standard language, and the community gave him the confidence to articulate his leadership skills in interviews. He landed a senior role with a 30% salary increase, a testament to how bridging that cultural gap makes a real, tangible difference.
Achieving an average job search timeline of 90 days or less is quite impressive. Could you explain the typical weekly workflow for a user on your platform, and how does the automation balance casting a wide net with ensuring each application is a high-quality, relevant match?
That 90-day timeline is something we’re incredibly proud of, and it comes from a philosophy of smart, not just mass, automation. A user’s week is transformed. Instead of spending hours scouring job boards and tweaking resumes, they might spend an hour or two at the beginning of the week reviewing the curated list of roles our AI has identified. They approve the matches they like, and our system takes over, tailoring and submitting applications. This frees them up to focus on what truly matters: interview preparation, networking, and upskilling. The balance comes from our machine learning algorithms. They don’t just match keywords; they learn a user’s preferences, career trajectory, and even the types of company cultures they thrive in. So while we apply to hundreds of roles, each one is a high-probability match, ensuring the net is cast wide but in the most fertile waters. This efficiency is how we achieve a 60% reduction in job search time for our users.
You mention tapping into the “hidden job market,” which is often relationship-driven. How does an AI-powered platform gain access to these unlisted opportunities, and what does the process look like for connecting your users with roles that aren’t available on standard job boards?
It’s a fantastic question because it highlights that technology alone isn’t enough; it needs to be augmented by human connection. Our AI is the scout. It analyzes market trends, executive movements, and company growth indicators to predict hiring needs before a role is ever publicly listed. This gives us data-driven insights on where to focus our networking efforts. We then leverage our established relationships with hiring managers and tech leaders—relationships built on trust and a track record of delivering top-tier talent. When we see a potential fit, we can directly present a curated list of our candidates to a hiring manager, completely bypassing the traditional application process. For the user, it feels seamless. They simply get an alert about an exclusive opportunity that they won’t find on LinkedIn or Indeed, one that’s been handpicked for them.
With over 500 placements and a 25% average salary increase for users, the results are compelling. Could you break down the critical factors that contribute to these successful financial outcomes and share an anecdote about a particularly challenging placement that your system helped facilitate?
The financial success stems from three critical factors. First, efficiency—by applying to more relevant jobs, our users get more interviews, which naturally leads to more offers and better negotiating power. Second, we eliminate underemployment. Our AI is very good at matching a candidate’s full skill set to roles that truly value their expertise, pushing them out of the overqualified-but-underpaid cycle. Third is confidence, which is fueled by our community and support. We had one user, a brilliant data scientist, who was stuck in a contract role for two years, convinced she couldn’t land a full-time position due to her visa status. The system not only found roles at visa-sponsoring companies but the mentorship she received helped her ace the interviews. She secured a permanent role at a top tech firm, not just with a significant pay bump but with the job security she and her family desperately needed. Seeing that transformation is what makes the 500+ placements feel so meaningful.
Your future plans include AI-powered career coaching. How do you envision this feature working alongside the automated application system, and what kind of personalized guidance will it offer to help a tech professional not only find their next job but also map out their long-term career growth?
We see AI career coaching as the next logical evolution, moving from finding a job to building a career. This feature will integrate directly with our existing system. As the AI tracks a user’s job search—the roles they are matched with, the interviews they get, the feedback they receive—it will identify patterns. It might notice a user is consistently getting interviews for a certain role but failing the technical assessment. The AI coach could then suggest specific upskilling courses or mock interview modules. It can also map out a five-year growth plan, analyzing market trends to advise on which certifications or skills will be most valuable in the future. It’s about providing proactive, data-driven guidance that helps a professional not just make their next move, but make every move a strategic step toward their ultimate career goals.
What is your forecast for the role of AI in the tech recruiting industry over the next five years?
Over the next five years, AI will become less of a tool and more of a co-pilot for both candidates and recruiters. We’ll move beyond simple automation and into predictive, hyper-personalized career management. For candidates, AI will act as a lifelong career agent, proactively suggesting upskilling opportunities, identifying internal promotion paths, and even flagging promising roles at other companies before the individual has even thought about leaving. For recruiters, AI will handle the vast majority of sourcing and screening, freeing them to focus entirely on the human elements: building relationships, assessing cultural fit, and selling the company’s vision. The result will be a more efficient, equitable, and human-centric hiring landscape, where technology empowers people to make better connections, faster.