Recruiting skilled talent in product engineering has always demanded significant attention. Over time, the process has become increasingly challenging due to the growing expectations placed on engineers and the expanding range of roles that fall under the umbrella of product development.
As a Founder & Product Engineering Head at Mavoix, I am directly responsible for identifying individuals who not only possess deep technical expertise but can also make meaningful contributions to innovation and execution.
Finding such candidates has proven to be far more complex than it appears. The process of screening, in particular, has consumed a significant amount of effort, time, and internal resources.
The Challenge of Technical Screening
Each time we open a position, we receive hundreds of resumes. Many of them appear impressive at a glance, but very few accurately reflect real-world engineering capabilities. Technical screening is designed to filter candidates based on their ability to perform effectively. However, the existing tools and processes often fall short in evaluating the aspects that matter most.
While traditional platforms offer coding tests or online assessments, these exercises are often generic. They do not accurately reflect the complexity of actual product environments or the challenges engineers face once they are onboarded. More importantly, such tools lack the ability to distinguish between surface-level knowledge and deep expertise. This often results in wasted interviews and suboptimal hiring decisions.
Searching for a Better Approach
For a long time, I explored new approaches and platforms that could help address this issue. Many recruitment platforms claim to offer AI-based solutions. However, on closer examination, most of them focus on automating workflows rather than understanding or evaluating technical skill in a meaningful way.
In many cases, the platform merely runs predefined scripts or matches keywords from resumes. These features may reduce effort in administrative areas, but they do not help assess whether a candidate is truly capable of solving technical problems, thinking critically about systems, or working collaboratively within a team on complex engineering challenges.
This is the gap that AI in technical hiring needs to fill by bringing a deeper level of intelligence into candidate assessment, beyond what automation can provide.
A Different Conversation
A few months ago, I had a conversation with Avi, a long-time friend and one of the co-founders of Hello Recruiter. We discussed the common challenges we encounter when hiring engineers. During our discussion, he introduced me to the hiring platform they are building.
I learned that Hello Recruiter is developing an AI-powered system specifically designed to evaluate talent across both technical and behavioral dimensions. Unlike traditional tools, their model is being trained to go beyond test scores and assess a candidate’s suitability for specific environments and team cultures.
The idea immediately caught my attention. I had been searching for a solution that could alleviate the burden on my team while enhancing the accuracy of our selection process. The way the Hello Recruiter platform approaches evaluation – by analyzing patterns, predicting candidate alignment, and minimizing bias – sounded more aligned with the kind of solution our industry needs.
As they move closer to launch, I decided to be one of the early users of their beta program. My hope is that through this collaboration, we will be able to streamline our hiring and make better decisions based on objective, actionable insights driven by AI in technical hiring.
The Complexity of Hiring in Product Engineering
Hiring in engineering is different from other sectors because of the layered nature of the skill sets involved. A typical candidate is expected to work across tools, frameworks, and methodologies. From clean code practices to knowledge of cloud systems, CI/CD pipelines, system design, and version control, the list continues to expand.
On top of this, we need engineers who can think independently, communicate with clarity, and align with the goals of the larger product. These competencies cannot be measured with static coding exercises or interviews that rely heavily on subjective judgment.
Another difficulty is that product engineering evolves rapidly. A candidate who appears well-versed today may quickly fall behind unless they are adaptable and driven by continuous learning. This means we must find individuals who are both technically sound and capable of growing with the role.
This complexity is what makes AI in technical hiring such a valuable area of innovation. The ability to analyze multi-dimensional profiles, predict fit, and learn from hiring outcomes is critical for long-term success.
What AI Can Bring to the Table?
When used effectively, AI can address several gaps in the recruitment process. Rather than simply processing large volumes of candidates quickly, the focus should be on identifying the most suitable candidates for each unique role.
Context-Aware Skill Assessment: AI can evaluate code, communication patterns, and historical performance to create a clearer picture of a candidate’s capability. Instead of testing for surface-level knowledge, the system can assess how the person approaches problems, follows logical structures, and implements solutions.
Intelligent Test Design: An AI-powered platform can generate adaptive test flows that align with the seniority of the role, the specific tech stack in use, and the actual complexity of the product being built. This ensures that the evaluation is both relevant and challenging.
Fairness and Transparency: Many hiring decisions are affected by unconscious bias. With a properly trained AI, we can anonymize evaluations and remove personal identifiers during screening. This can help ensure that candidates are being assessed for what they can do, not for where they studied or which companies they have worked for in the past.
Better Use of Engineering Time: One of the biggest advantages of AI in technical hiring is time optimization. Our engineers spend less time on manual screening and repetitive interviews, allowing them to stay focused on building products. At the same time, the hiring process becomes faster and more data-driven.
Why Hello Recruiter Stands Out?
What makes Hello Recruiter’s approach different is its focus on learning and context. From the early conversations I have had with their team, I can see that the platform is being developed to work with real-life hiring use cases and feedback from practitioners.
Instead of offering a rigid solution, Hello Recruiter aims to allow customization, calibration, and continuous learning. The AI does not just filter resumes or track interview outcomes. It builds profiles, matches expectations with reality, and helps hiring managers make better decisions.
As someone responsible for driving innovation, I appreciate platforms that evolve with input and operate with transparency. TThis is one of the reasons I chose to participate in their beta testing phase. I believe Hello Recruiter will shape the next generation of AI in technical hiring.
What I Hope to Gain
As part of Hello Recruiter’s early user group, I look forward to testing their tools across several open positions. My key expectations are:
More accurate identification of candidates who match our tech stack and problem-solving needs.
Reduced time spent by senior engineers on evaluating basic skills.
Insights on how candidates think, not just what they know.
An unbiased, data-driven approach to comparing applicants.
A more streamlined experience for both our team and the candidates.
If the platform delivers on these, I believe it will not only save time but also improve the quality of hires significantly.
Closing Thoughts
Recruiting engineers is a critical responsibility that cannot be left to chance. The cost of hiring the wrong person is high, not only in terms of money, but also in terms of team productivity and product quality.
In this environment, AI in technical hiring is not a futuristic concept. It is a practical necessity. With the right tools, we can focus on what truly matters—building great teams that solve meaningful problems.
Artificial Intelligence, when applied responsibly, can play a major role in solving this. It has the potential to remove guesswork, eliminate repetitive manual tasks, and support hiring teams with clear and reliable insights.
My collaboration with Hello Recruiter comes at a time when we are scaling and looking for tools that can help us maintain our standards without slowing down our growth. I am optimistic that their platform will bring real value to companies like ours, and I look forward to sharing our experience once we have gone through the pilot phase.
You can get in touch with the experts at Hello Recruiter to learn more about their platform.
AI in Recruitment, Technical Assessment, Product Engineering, Hiring Tech Talent, AI for HR, Candidate Evaluation
Founder & Product Engineering Head
