Forecasting Tech Hiring Trends For 2023 With 6 Experts

2023 is here, and it is time to look ahead. Start planning your tech hiring needs as per your business requirements, revamp your recruiting processes, and come up with creative ways to land that perfect “unicorn candidate”!

Right? Well, jumping in blindly without heeding what this year holds for you can be a mistake. So before you put together your plans, ask yourselves this—What are the most important 2023 recruiting trends in tech hiring that you should be prepared for? What are the predictions that will shape this year?

We went around and posed three important questions to industry experts that were on our minds. And what they had to say certainly gave us some food for thought!

Before we dive in, allow me to introduce you to our expert panel of six, who had so much to say from personal experience!

Meet the Expert Panel

Radoslav Stankov has more than 20 years of experience working in tech. He is currently Head of Engineering at Product Hunt. Enjoys blogging, conference speaking, and solving problems.

Mike “Batman” Cohen is the Founder of Wayne Technologies, a Sourcing-as-a-Service company providing recruitment data and candidate outreach services to enhance the talent acquisition journey.

Pamela Ilieva is the Director of International Recruitment at Shortlister, a platform that connects employers to wellness, benefits, and HR tech vendors.

Brian H. Hough is a Web2 and Web3 software engineer, AWS Community Builder, host of the Tech Stack Playbook™ YouTube channel/podcast, 5-time global hackathon winner, and tech content creator with 10k+ followers.

Steve O'Brien is Senior Vice President, Talent Acquisition at Syneos Health, leading a global team of top recruiters across 30+ countries in 24+ languages, with nearly 20 years of diverse recruitment experience.

Patricia (Sonja Sky) Gatlin is a New York Times featured activist, DEI Specialist, EdTechie, and Founder of Newbies in Tech. With 10+ years in Higher Education and 3+ in Tech, she now works part-time as a Diversity Lead recruiting STEM professionals to teach gifted students.

Overview of the upcoming tech industry landscape in 2024

Continued emphasis on remote work and flexibility: As we move into 2024, the tech industry is expected to continue embracing remote work and flexible schedules. This trend, accelerated by the COVID-19 pandemic, has proven to be more than a temporary shift. Companies are finding that remote work can lead to increased productivity, a broader talent pool, and better work-life balance for employees. As a result, recruiting strategies will likely focus on leveraging remote work capabilities to attract top talent globally.

Rising demand for AI and Machine Learning Skills: Artificial Intelligence (AI) and Machine Learning (ML) continue to be at the forefront of technological advancement. In 2024, these technologies are expected to become even more integrated into various business processes, driving demand for professionals skilled in AI and ML. Companies will likely prioritize candidates with expertise in these areas, and there may be an increased emphasis on upskilling existing employees to meet this demand.

Increased focus on cybersecurity: With the digital transformation of businesses, cybersecurity remains a critical concern. The tech industry in 2024 is anticipated to see a surge in the need for cybersecurity professionals. Companies will be on the lookout for talent capable of protecting against evolving cyber threats and ensuring data privacy.

Growth in cloud computing and edge computing: Cloud computing continues to grow, but there is also an increasing shift towards edge computing – processing data closer to where it is generated. This shift will likely create new job opportunities and skill requirements, influencing recruiting trends in the tech industry.

Sustainable technology and green computing: The global emphasis on sustainability is pushing the tech industry towards green computing and environmentally friendly technologies. In 2024, companies may seek professionals who can contribute to sustainable technology initiatives, adding a new dimension to tech recruiting.

Emphasis on soft skills: While technical skills remain paramount, soft skills like adaptability, communication, and problem-solving are becoming increasingly important. Companies are recognizing the value of these skills in fostering innovation and teamwork, especially in a remote or hybrid work environment.

Diversity, Equity, and Inclusion (DEI): There is an ongoing push towards more diverse and inclusive workplaces. In 2024, tech companies will likely continue to strengthen their DEI initiatives, affecting how they recruit and retain talent.

6 industry experts predict the 2023 recruiting trends

#1 We've seen many important moments in the tech industry this year...

Rado: In my opinion, a lot of those will carry over. I felt this was a preparation year for what was to come...

Mike: I wish I had the crystal ball for this, but I hope that when the market starts picking up again...

Pamela: Quiet quitting has been here way before 2022, and it is here to stay if organizations and companies...

Pamela Ilieva, Director of International Recruitment, Shortlister

Also, read: What Tech Companies Need To Know About Quiet Quitting

Brian: Yes, absolutely. In the 2022 Edelman Trust Barometer report...

Steve: Quiet quitting in the tech space will naturally face pressure as there is a redistribution of tech talent...

Patricia: Quiet quitting has been around for generations—people doing the bare minimum because they are no longer incentivized...

Patricia Gatlin, DEI Specialist and Curator, #blacklinkedin

#2 What is your pro tip for HR professionals/engineering managers...

Rado: Engineering managers should be able to do "more-with-less" in the coming year.

Radoslav Stankov, Head of Engineering, Product Hunt

Mike: Well first, (shameless plug), be in touch with me/Wayne Technologies as a stop-gap for when the time comes.

Mike “Batman” Cohen, Founder of Wayne Technologies

It's in the decrease and increase where companies find the hardest challenges...

Pamela: Remain calm – no need to “add fuel to the fire”!...

Brian: We have to build during the bear markets to thrive in the bull markets.

Companies can create internal hackathons to exercise creativity...

Also, read: Internal Hackathons - Drive Innovation And Increase Engagement In Tech Teams

Steve: HR professionals facing a hiring freeze will do well to “upgrade” processes, talent, and technology aggressively during downtime...

Steve O'Brien, Senior Vice President, Talent Acquisition at Syneos Health

Patricia: Talk to hiring managers in all your departments. Ask, what are the top 3-5 roles they are hiring for in the new year?...

Also, watch: 5 Recruiting Tips To Navigate The Hiring Freeze With Shalini Chandra, Senior TA, HackerEarth

#3 What top 3 skills would you like HR professionals/engineering managers to add to their repertoire in 2023 to deal with upcoming challenges?

6 industry experts predict the 2023 recruiting trends

Rado: Prioritization, team time, and environment management.

I think "prioritization" and "team time" management are obvious. But what do I mean by "environment management"?

A productive environment is one of the key ingredients for a productive team. Look at where your team wastes most time, which can be automated. For example, end-to-end writing tests take time because our tools are cumbersome and undocumented. So let's improve this.

Mike: Setting better metrics/KPIs, moving away from LinkedIn, and sharing more knowledge.

Metrics/KPIs: Become better at setting measurable KPIs and accountable metrics. They are not the same thing—it's like the Square and Rectangle. One fits into the other but they're not the same. Hold people accountable to metrics, not KPIs. Make sure your metrics are aligned with company goals and values, and that they push employees toward excellence, not mediocrity.
Freedom from LinkedIn: This is every year, and will probably continue to be. LinkedIn is a great database, but it is NOT the only way to find candidates, and oftentimes, not even the most effective/efficient. Explore other tools and methodologies!
Join the conversation: I'd love to see new names of people presenting at conferences and webinars. And also, see new authors on the popular TA content websites. Everyone has things they can share—be a part of the community, not just a user of. Join FB groups, write and post articles, and comment on other people's posts with more than 'Great article'. It's a great community, but it's only great because of the people who contribute to it—be one of those people.

Pamela: Resilience, leveraging data, and self-awareness.

Resilience: A “must-have” skill for the 21st century due to constant changes in the tech industry. Face and adapt to challenges. Overcome them and handle disappointments. Never give up. This will keep HR people alive in 2023.
Data skills: Get some data analyst skills. The capacity to transfer numbers into data can help you be a better HR professional, prepared to improve the employee experience and show your leadership team how HR is leveraging data to drive business results.
Self-awareness: Allows you to react better to upsetting situations and workplace challenges. It is a healthy skill to cultivate – especially as an HR professional.

Also, read: Diving Deep Into The World Of Data Science With Ashutosh Kumar

Brian: Agility, resourcefulness, and empathy.

Agility: Allows professionals to move with market conditions. Always be as prepared as possible for any situation to come. Be flexible based on what does or does not happen.
Resourcefulness: Allows professionals to do more with less. It also helps them focus on how to amplify, lift, and empower the current teams to be the best they can be.
Empathy: Allows professionals to take a more proactive approach to listening and understanding where all workers are coming from. Amid stressful situations, companies need empathetic team members and leaders alike who can meet each other wherever they are and be a support.

Steve: Negotiation, data management, and talent development.

Negotiation: Wage transparency laws will fundamentally change the compensation conversation. We must ensure we are still discussing compensation early in the process. And not just “assume” everyone’s on the same page because “the range is published”.
Data management and predictive analytics: Looking at your organization's talent needs as a casserole of indistinguishable components and demands will not be good enough. We must upgrade the accuracy and consistency of our data and the predictions we can make from it.

Also, read: The Role of Talent Intelligence in Optimizing Recruitment

Talent development: We’ve been exploring the interplay between TA and TM for years. Now is the time to integrate your internal and external talent marketplaces. To provide career experiences to people within your organization and not just those joining your organization.

Patricia: Technology, research, and relationship building.

Technology: Get better at understanding the technology that’s out there. To help you speed up the process, track candidate experience, but also eliminate bias. Metrics are becoming big in HR.
Research: Honestly, read more books. Many great thought leaders put out content about the “future of work”, understanding “Gen Z”, or “quiet quitting.” Dedicate work hours to understanding your ever-changing field.
Relationship Building: Especially in your immediate communities. Most people don’t know who you are or what exactly it is that you do. Build your personal brand and what you are doing at your company to impact those closest to you. Create a referral funnel to get a pipeline going. When people want a job you and your company ought to be top of mind. Also, tell the stories of the people that work there.

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Hackathons

Vibe Coding: Shaping the Future of Software

A New Era of CodeVibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today,...

A New Era of Code

Vibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today, when code is produced quickly through AI, the true value lies in designing, refining, and optimizing systems. Our role now goes beyond writing code; we must also ensure that our systems remain efficient and reliable.

From Machine Language to Natural Language

I recall the early days when every line of code was written manually. We progressed from machine language to high-level programming, and now we are beginning to interact with our tools using natural language. This development does not only increase speed but also changes how we approach problem solving. Product managers can now create working demos in hours instead of weeks, and founders have a clearer way of pitching their ideas with functional prototypes. It is important for us to rethink our role as developers and focus on architecture and system design rather than simply on typing c

The Promise and the Pitfalls

I have experienced both sides of vibe coding. In cases where the goal was to build a quick prototype or a simple internal tool, AI-generated code provided impressive results. Teams have been able to test new ideas and validate concepts much faster. However, when it comes to more complex systems that require careful planning and attention to detail, the output from AI can be problematic. I have seen situations where AI produces large volumes of code that become difficult to manage without significant human intervention.

AI-powered coding tools like GitHub Copilot and AWS’s Q Developer have demonstrated significant productivity gains. For instance, at the National Australia Bank, it’s reported that half of the production code is generated by Q Developer, allowing developers to focus on higher-level problem-solving . Similarly, platforms like Lovable enable non-coders to build viable tech businesses using natural language prompts, contributing to a shift where AI-generated code reduces the need for large engineering teams. However, there are challenges. AI-generated code can sometimes be verbose or lack the architectural discipline required for complex systems. While AI can rapidly produce prototypes or simple utilities, building large-scale systems still necessitates experienced engineers to refine and optimize the code.

The Economic Impact

The democratization of code generation is altering the economic landscape of software development. As AI tools become more prevalent, the value of average coding skills may diminish, potentially affecting salaries for entry-level positions. Conversely, developers who excel in system design, architecture, and optimization are likely to see increased demand and compensation.
Seizing the Opportunity

Vibe coding is most beneficial in areas such as rapid prototyping and building simple applications or internal tools. It frees up valuable time that we can then invest in higher-level tasks such as system architecture, security, and user experience. When used in the right context, AI becomes a helpful partner that accelerates the development process without replacing the need for skilled engineers.

This is revolutionizing our craft, much like the shift from machine language to assembly to high-level languages did in the past. AI can churn out code at lightning speed, but remember, “Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” Use AI for rapid prototyping, but it’s your expertise that transforms raw output into robust, scalable software. By honing our skills in design and architecture, we ensure our work remains impactful and enduring. Let’s continue to learn, adapt, and build software that stands the test of time.

Ready to streamline your recruitment process? Get a free demo to explore cutting-edge solutions and resources for your hiring needs.

Tech Assessment

Guide to Conducting Successful System Design Interviews in 2025

What is Systems Design?Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.Systems Design, in its...

What is Systems Design?

Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.

Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.

Systems Design, in its essence, is a blueprint of how software and applications should work to meet specific goals. The multi-dimensional nature of this discipline makes it open-ended – as there is no single one-size-fits-all solution to a system design problem.

What is a System Design Interview?

Conducting a System Design interview requires recruiters to take an unconventional approach and look beyond right or wrong answers. Recruiters should aim for evaluating a candidate’s ‘systemic thinking’ skills across three key aspects:

How they navigate technical complexity and navigate uncertainty
How they meet expectations of scale, security and speed
How they focus on the bigger picture without losing sight of details

This assessment of the end-to-end thought process and a holistic approach to problem-solving is what the interview should focus on.

What are some common topics for a System Design Interview

System design interview questions are free-form and exploratory in nature where there is no right or best answer to a specific problem statement. Here are some common questions:

How would you approach the design of a social media app or video app?

What are some ways to design a search engine or a ticketing system?

How would you design an API for a payment gateway?

What are some trade-offs and constraints you will consider while designing systems?

What is your rationale for taking a particular approach to problem solving?

Usually, interviewers base the questions depending on the organization, its goals, key competitors and a candidate’s experience level.

For senior roles, the questions tend to focus on assessing the computational thinking, decision making and reasoning ability of a candidate. For entry level job interviews, the questions are designed to test the hard skills required for building a system architecture.

The Difference between a System Design Interview and a Coding Interview

If a coding interview is like a map that takes you from point A to Z – a systems design interview is like a compass which gives you a sense of the right direction.

Here are three key difference between the two:

Coding challenges follow a linear interviewing experience i.e. candidates are given a problem and interaction with recruiters is limited. System design interviews are more lateral and conversational, requiring active participation from interviewers.

Coding interviews or challenges focus on evaluating the technical acumen of a candidate whereas systems design interviews are oriented to assess problem solving and interpersonal skills.

Coding interviews are based on a right/wrong approach with ideal answers to problem statements while a systems design interview focuses on assessing the thought process and the ability to reason from first principles.

How to Conduct an Effective System Design Interview

One common mistake recruiters make is that they approach a system design interview with the expectations and preparation of a typical coding interview.
Here is a four step framework technical recruiters can follow to ensure a seamless and productive interview experience:

Step 1: Understand the subject at hand

Develop an understanding of basics of system design and architecture
Familiarize yourself with commonly asked systems design interview questions
Read about system design case studies for popular applications
Structure the questions and problems by increasing magnitude of difficulty

Step 2: Prepare for the interview

Plan the extent of the topics and scope of discussion in advance
Clearly define the evaluation criteria and communicate expectations
Quantify constraints, inputs, boundaries and assumptions
Establish the broader context and a detailed scope of the exercise

Step 3: Stay actively involved

Ask follow-up questions to challenge a solution
Probe candidates to gauge real-time logical reasoning skills
Make it a conversation and take notes of important pointers and outcomes
Guide candidates with hints and suggestions to steer them in the right direction

Step 4: Be a collaborator

Encourage candidates to explore and consider alternative solutions
Work with the candidate to drill the problem into smaller tasks
Provide context and supporting details to help candidates stay on track
Ask follow-up questions to learn about the candidate’s experience

Technical recruiters and hiring managers should aim for providing an environment of positive reinforcement, actionable feedback and encouragement to candidates.

Evaluation Rubric for Candidates

Facilitate Successful System Design Interview Experiences with FaceCode

FaceCode, HackerEarth’s intuitive and secure platform, empowers recruiters to conduct system design interviews in a live coding environment with HD video chat.

FaceCode comes with an interactive diagram board which makes it easier for interviewers to assess the design thinking skills and conduct communication assessments using a built-in library of diagram based questions.

With FaceCode, you can combine your feedback points with AI-powered insights to generate accurate, data-driven assessment reports in a breeze. Plus, you can access interview recordings and transcripts anytime to recall and trace back the interview experience.

Learn how FaceCode can help you conduct system design interviews and boost your hiring efficiency.

AI Recruiting

How Candidates Use Technology to Cheat in Online Technical Assessments

Impact of Online Assessments in Technical Hiring In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers. The ease and...

Impact of Online Assessments in Technical Hiring

In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers.

The ease and efficiency of virtual interviews, take home programming tests and remote coding challenges is transformative. Around 82% of companies use pre-employment assessments as reliable indicators of a candidate's skills and potential.

Online skill assessment tests have been proven to streamline technical hiring and enable recruiters to significantly reduce the time and cost to identify and hire top talent.

In the realm of online assessments, remote assessments have transformed the hiring landscape, boosting the speed and efficiency of screening and evaluating talent. On the flip side, candidates have learned how to use creative methods and AI tools to cheat in tests.

As it turns out, technology that makes hiring easier for recruiters and managers - is also their Achilles' heel.

Cheating in Online Assessments is a High Stakes Problem

With the proliferation of AI in recruitment, the conversation around cheating has come to the forefront, putting recruiters and hiring managers in a bit of a flux.

According to research, nearly 30 to 50 percent of candidates cheat in online assessments for entry level jobs. Even 10% of senior candidates have been reportedly caught cheating.

The problem becomes twofold - if finding the right talent can be a competitive advantage, the consequences of hiring the wrong one can be equally damaging and counter-productive.

As per Forbes, a wrong hire can cost a company around 30% of an employee's salary - not to mention, loss of precious productive hours and morale disruption.

The question that arises is - "Can organizations continue to leverage AI-driven tools for online assessments without compromising on the integrity of their hiring process? "

This article will discuss the common methods candidates use to outsmart online assessments. We will also dive deep into actionable steps that you can take to prevent cheating while delivering a positive candidate experience.

Common Cheating Tactics and How You Can Combat Them

Using ChatGPT and other AI tools to write code
Copy-pasting code using AI-based platforms and online code generators is one of common cheat codes in candidates' books. For tackling technical assessments, candidates conveniently use readily available tools like ChatGPT and GitHub. Using these tools, candidates can easily generate solutions to solve common programming challenges such as:
- Debugging code
- Optimizing existing code
- Writing problem-specific code from scratch
Ways to prevent it
- Enable full-screen mode
- Disable copy-and-paste functionality
- Restrict tab switching outside of code editors
- Use AI to detect code that has been copied and pasted
Enlist external help to complete the assessment

Candidates often seek out someone else to take the assessment on their behalf. In many cases, they also use screen sharing and remote collaboration tools for real-time assistance.

In extreme cases, some candidates might have an off-camera individual present in the same environment for help.

Ways to prevent it
- Verify a candidate using video authentication
- Restrict test access from specific IP addresses
- Use online proctoring by taking snapshots of the candidate periodically
- Use a 360 degree environment scan to ensure no unauthorized individual is present
Using multiple devices at the same time

Candidates attempting to cheat often rely on secondary devices such as a computer, tablet, notebook or a mobile phone hidden from the line of sight of their webcam.

By using multiple devices, candidates can look up information, search for solutions or simply augment their answers.

Ways to prevent it
- Track mouse exit count to detect irregularities
- Detect when a new device or peripheral is connected
- Use network monitoring and scanning to detect any smart devices in proximity
- Conduct a virtual whiteboard interview to monitor movements and gestures
Using remote desktop software and virtual machines

Tech-savvy candidates go to great lengths to cheat. Using virtual machines, candidates can search for answers using a secondary OS while their primary OS is being monitored.

Remote desktop software is another cheating technique which lets candidates give access to a third-person, allowing them to control their device.

With remote desktops, candidates can screen share the test window and use external help.

Ways to prevent it
- Restrict access to virtual machines
- AI-based proctoring for identifying malicious keystrokes
- Use smart browsers to block candidates from using VMs

Future-proof Your Online Assessments With HackerEarth

HackerEarth's AI-powered online proctoring solution is a tested and proven way to outsmart cheating and take preventive measures at the right stage. With HackerEarth's Smart Browser, recruiters can mitigate the threat of cheating and ensure their online assessments are accurate and trustworthy.

Secure, sealed-off testing environment
AI-enabled live test monitoring
Enterprise-grade, industry leading compliance
Built-in features to track, detect and flag cheating attempts

Boost your hiring efficiency and conduct reliable online assessments confidently with HackerEarth's revolutionary Smart Browser.