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Senior vs Junior Developers Hiring Process - Comparison & Differences

Senior vs Junior Developers Hiring Process - Comparison & Differences

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Arpit Mishra
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October 27, 2017
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5 min read
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A report on the National Employability of Engineers released last year by Aspiring Minds showed that a mere 3.67% of software engineers are employable for large-sized companies. Other statistics show that 90.72% of graduating engineers do not have the programming and algorithm skills desired by IT product companies, 72.77% lack soft-skills, and 59.40% lack cognitive skills.

With such dismal numbers, how do you test developers who are graduate or senior engineers with the right mix of skills to fulfill your requirements? In this article, we will talk about the hiring process for developers with the required talent for your company and what to focus on when hiring fresh and senior engineers.

Regardless of the level, you’re recruiting for, the first step is the same — defining your requirements in the form of skills needed and roles and responsibilities to be performed.

“Alice: Would you tell me, please, which way I ought to go from here?
The Cheshire Cat: That depends a good deal on where you want to get to.
Alice: I don’t much care where.
The Cheshire Cat: Then it doesn’t much matter which way you go.” – Lewis Carroll, Alice in Wonderland

Just like Alice, you will have trouble getting to your destination — finding the perfect candidates — if the path or requirements are not well-defined. Once you have defined the requirements, you can start the hiring process for your candidates.

Difference between senior and junior developers

Understanding the distinction between senior and junior developers is crucial for tailoring the hiring process effectively. These differences span various aspects, including:

Aspect
Junior Developers
Senior Developers
Experience and Skill Level
  • Less experience, often starting out or with a few years of professional experience.
  • Skills are foundational, focused on learning and growing within the role.
  • Extensive experience, often several years in the industry.
  • Advanced technical skills and deep understanding of programming languages, frameworks, and systems.
  • Capable of handling complex tasks with minimal supervision.
Problem-solving and Complexity
  • Developing problem-solving skills.
  • Suited for well-defined, less complex tasks.
  • Often require guidance to troubleshoot and solve problems.
  • Strong problem-solving skills, capable of tackling complex, ambiguous problems.
  • Can foresee potential issues and propose effective, scalable solutions.
Project Leadership and Mentoring
  • Not expected to lead projects or mentor others.
  • Focus on learning from others and gradually taking on more responsibility.
  • Often take on leadership roles within projects.
  • Mentor junior team members, provide guidance, and responsible for significant decision-making.
Autonomy and Decision Making
  • Require more oversight and direction.
  • Work often needs to be reviewed and validated by more experienced team members.
  • Operate with a high degree of autonomy.
  • Trusted to make critical decisions and often responsible for significant portions of a project or entire projects.
Contribution to Strategy and Planning
  • Focus on task execution, not heavily involved in strategic planning or high-level decision-making.
  • Play a key role in strategy, planning, and shaping the direction of projects.
  • Contribute to the broader technical strategy of the team or organization.
Salary and Investment
  • Command lower salaries, represent an investment in potential and growth within the company.
  • Have higher salary expectations, reflecting their experience and value in terms of expertise and leadership.
Cultural and Team Dynamics
  • Often bring fresh perspectives and new energy to a team, beneficial for team dynamics and innovation.
  • Experience significantly influences team culture and dynamics.
  • Often set technical standards and best practices within the team.

Hiring Process for a Fresh Graduate

Since a degree is clearly not a relevant measure of employability, it is critical that the hiring process is able to ascertain in other ways whether the candidate has the right skills and is a good fit for the company. It should check whether the candidate has technical acumen along with necessary soft skills such as the communication and interpersonal skills to work in a team. The hiring process for a fresh engineer looks something like this:

Sourcing

The first step in the hiring process is to source the right candidates for the job. You could try campus placements, use outside recruiters who do the sourcing for you or use inbound recruitment techniques to attract the right candidates. Any or all of these sources could give you a pool of candidates for consideration.

in this FastCompany article, Keawe Block, a recruiter at Google, says that they look for candidates who have experience at hackathons, coding competitions, or have had programming assignments at work. Check the resumes to see what coding languages they know, and what relevant internships they might have done. These give an insight into their technical acumen which can be tested further in the next stages.

Screening

You have a targeted pool of potential recruits. The next step is to filter them further by testing these candidates on their technical skills. Alternatively, you can use tools (such as HackerEarth Recruit) which have an online coding test, that allows you to check scores in real-time and use detailed test reports to analyze performance.

Selection

Depending on the job requirement, this could be an interview or a series of interviews with supervisors and peers. If your engineers are expected to work in an agile environment, your questions should check for whether the candidate is a team player, is patient, and resilient as she would be working for long periods of time with the rest of the team. Check mainly for “fit,” whether you see the person blending in and growing with the company.

Lastly, it does not matter if the candidate is not a full-stack developer, as long as she demonstrates a willingness to learn and has the right attitude. Technical requirements of companies are ever-changing, and any skills one has today might be rendered redundant tomorrow.

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Hiring Process for a Senior Developer

The hiring process for a senior developer differs vastly from that of a fresh graduate. For starters, the emphasis is on experience and accomplishments in past roles. The other vital difference is in sourcing senior managers, which is much more challenging because of the limited pool of qualified senior engineers available.

The hiring process for a senior developer looks something like this:

Sourcing

With fresh engineers, there is a problem of plenty; with senior engineers, the opposite holds true. There are few engineers at the senior level who have skills that you need, and they might not be motivated to switch jobs. Referrals are the perhaps the best approach to attract candidates in this case as they referrals a mutual interest from both the employer and the potential hire. You can also use inbound recruitment techniques, such as your website and social media handles, to advertise and invite candidates to apply. Alternatively, you can use recruiters to do the sourcing for you.

Screening

The quickest way to screen candidates is to conduct telephonic interviews where you can ask them for further details about their experience and skills. A more detailed way to check their acumen would be to assign a coding test, allocate some time to work on it and do a review with them. This gives you a chance to see them in action and judge their ability in a practical manner.

Selection

The selection involves interviews with the top management. The number of interviews is usually lesser for a senior engineer than a fresh graduate. The interview will focus on the candidate’s experience and how that might be relevant to the role that the candidate is being interviewed for. The interview should focus on how he has demonstrated leadership skills in the past with relevant examples. A candidate that attends conferences and technology meet-ups indicates that she’s in touch with changing technology trends.

No One-Size-Fits-all-Solution

Since the requirements for graduates and senior engineers are different, the skills tested and the hiring process cannot be the same for both. While you look for leadership skills, stability, and relevant experience for a senior engineer; you look for aptitude, a willingness to learn, and culture fit while hiring fresh engineers. As stated above, it all needs to tie back to the company’s requirements. A vital point of difference is also negotiations with senior candidates. It is difficult to make the switch if they don’t get the salary they’re looking for. With fresh graduates, because of the abundant supply, it is possible to find someone in your budget, but with senior engineers, the salary must be lucrative enough, hence the negotiations take longer.

If you are looking for a recruitment solution to efficiently hire fresh and senior talent for your organization, sign up for a free trial of HackerEarth Recruit

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Author
Arpit Mishra
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October 27, 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 code.

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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