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Why do so many engineers hate their jobs?

Why do so many engineers hate their jobs?

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Dhanya Menon
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November 24, 2017
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5 min read
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It wouldn’t be too presumptuous to say that half the population considers their jobs are just to get them by. Forbes says 52.3% are unhappy at work, and 63% are not engaged in their jobs. People who are over 35 (says Robert Half) seem to be more listless and unhappy than their younger colleagues who still have some of the stardust in their eyes. Alright, so most people don’t enjoy their jobs. Not news, is it?

Engineers don’t have a better story to tell either. The ennui or disillusionment seems to be a part of their work lives. Even as we are moving from a reactive economy to a predictive one, engineering remains one of the more coveted professions. It now offers degrees that are quite versatile, with enough job roles waiting for you to try. However, many engineers have voted for job dissatisfaction for various reasons, in informal polls .

What makes them unhappy?

Overworked, over-enthusiastic

Most engineers will agree that they tend to feel burned out faster because of a number of hours they put in, especially in the initial days of the job. Long work hours can take a toll on their personal lives, fitness, health, and mental well-being. Although some people simply aren’t willing to put in more than 40 hours a week, there are a few eager beavers trying to impress management or the truly passionate ones who spend a lot of focused hours at the office. The upside is that these engineers who “outwork” their colleagues do typically get ahead quicker. The downside is that they can become disenchanted in no time if they don’t see any tangible results, not to mention becoming unwell over time.

What the company can do:

Appreciate the engineers who show up early and stay late, doing productive work to meet deadlines. But encourage a healthy work-life balance for all your employees by providing exercise access, company outings, recreational areas, community engagement activities, flexible schedules, team building events, training or workshops, and childcare facilities. In the long run, your company will be more attractive to potential hires. Also, you can improve employee retention and be home to loyal, better-quality workers.


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Underpaid, undervalued

Engineers in big tech firms may not identify with this because they tend to enjoy several benefits above-market compensation brings. On the whole, we recognize the engineering profession as one that guarantees financial security. And many engineers feel that they are, more or less, being paid adequately for the job they do. But in fledgling firms, this isn’t always the case. Apart from the insane hours, engineers are on their toes all the time trying to fix issues, whether it is complex machinery or code, before they escalate. The young engineering graduates often complain that their appraisals follow a bell-curve. In this infographic, 50.4% of engineers said they were qualified enough to make more money.

What the company can do:

Offer qualified engineers a decent compensation; a griping lot will negatively impact productivity and company morale. As an engineering firm, ensure that you have proper work scheduling and project management in place. In startups, engineers often feel that they are grossly underpaid (some are overpaid!) after working almost 70 to 80 hours per week. Losing skilled tech talent to the competition is easily avoided by ensuring fairness in your hiring practices and in your efforts to retain, recognize, and reward.

Under-prepared, confused

Young graduates come into jobs excited and hoping to become Q (from James Bond) and change the world. But in reality, they become disgruntled by having to deal with dull tasks like checking for inconsistencies in sheet numbers across design drafts. Some of them even quit the profession few months after realizing that either they were ill-informed or that engineering was much better at the Uni. According to Michael MacRae (ASME), engineers are “tasked with projects that require technical skills without also providing an environment offering collaboration, problem-solving, and other perks that satisfy the engineering mind and soul.”This is also cited as a reason, because these graduates are not prepared enough for all that the job requires them to do.

What the company can do:

Remember to outline the exact responsibilities that define a role at the outset. Make them understand that along with interesting tasks, some gray jobs will be part of the position. Tell them what opportunities for upward mobility exist. Clearly chalk out a plan for advancement for technical staff. Create a positive work environment with helpful, patient senior staff or experts to smoothen any wrinkles. Invest in your employee, and you will see how their appreciation translates into personal and company growth. Also, remember to have dedicated personnel to liaise with the engineers and other non-technical staff to minimize conflicts and lack of clarity between requirements and expected solutions.

Apart from these, what else can companies do to keep their engineers happy?

Cultivating a cooperative and positive workplace atmosphere

Encourage professional growth and skill advancement among your team. Foster a climate that prioritizes teamwork and the exchange of knowledge to resolve conflicts and boost collaboration. Establish an environment grounded in mutual respect, where each member feels appreciated and supported. Promote transparent and collaborative communication within the team. Explore literature like “Radical Candor” by Kim Scott, and “Extreme Ownership” by Jocko Willink and Leif Babin for further inspiration.

Elevating code quality and sustainability

Begin by instituting code review methodologies (such as mob/pair programming or pull requests) to guarantee adherence to best practices and superior code quality. Prioritize automated testing to identify issues early and confirm code accuracy. Plan for ongoing enhancements and allocate time for substantial refactoring and addressing technical debt to boost code sustainability. Encourage, or even mandate, comprehensive documentation in everyday tasks to improve clarity and ease of ongoing maintenance.

Refining recruitment and interview techniques

Recognize that many engineers struggle with conducting interviews. Select and train a group specifically for interviewing, focusing on effective and impartial methods. Develop a structured interview process that assesses candidates on relevant skills and problem-solving capabilities, steering clear of irrelevant challenges. Always offer constructive feedback to applicants to guide their development, regardless of hiring decisions.

Advocating for work-life harmony and employee wellness

Promote a culture that values the balance between work and personal life, and supports employee well-being. This includes refraining from late-night communications and offering flexible working conditions, especially as many in software engineering find remote or adaptable work more productive and enjoyable. Encourage breaks, physical activities, and screen-free time in innovative ways, such as scheduling meetings for slightly shorter durations. Provide support and resources for mental and physical health.

Encouraging ongoing improvement and learning

Highlight the significance of innovation, experimentation, and staying informed about industry developments. Build a learning-focused culture, offering groups for skill development, book clubs, and open training sessions. Motivate staff to embrace new technologies and enhance their abilities, potentially incorporating learning into performance reviews. Ensure there are methods to objectively evaluate and recognize continuous learning and skill development.

Streamlining operations and minimizing bureaucracy

Assess and refine internal processes to cut down on unnecessary meetings, bureaucratic hurdles, and inefficient practices. Give teams more autonomy in decision-making and reduce unnecessary approval steps, handoffs, reviews, or other procedural inefficiencies. Adopt agile methodologies to foster a more flexible, efficient, and adaptable work environment.

Championing diversity and inclusivity

Work towards creating a welcoming atmosphere for people from various backgrounds. Actively pursue diversity and inclusivity within the organization. If not already in place, implement policies and practices that ensure equal opportunities for all employees.

Although the perks and compensation for tech-related jobs in big companies can be really attractive, cookie-cutter corporate environments may not work for some. Respect your engineers and empower them. Along with flexible work schedules, give them some autonomy and listen to their opinions. Give them the freedom to solve problems via innovative approaches in a results-driven culture. Groom them for leadership roles and train them on the managerial skills required to climb the ladder. Support their work-related interests and give them opportunities for career progression via access to and training on new tools and technologies. Conduct internal hackathons and other challenges to boost employee engagement by helping employees showcase their skills and foster collaboration and innovation. Recognize their contributions and ensure they see what difference their work is making to the company or the community.

If none of these work, then ask them what they need to be happy and productive. That has to work!

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Author
Dhanya Menon
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November 24, 2017
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5 min read
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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.

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.

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


  1. 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
  2. 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
  3. 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
  4. 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.
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