How to apply for Software Engineering Internships at startups

With the beginning of new year, every startup’s open mailing list starts receiving emails from graduate students for summer internship. I have read hundreds of applications that follow a generic template, somewhat like this:

Dear Sir/Ma'am,

My name is and I am currently pursuing my in from . I am well-versed with C/C++ and have started learning Java. I’m also learning about Android and iOS apps. I have good knowledge of HTML, CSS, JS too.

If given chance, I’ll give my 100% at work. I am confident that I will be a valuable asset to your team.

Please find the attachment of my CV

Kind regards,

Seems like a decent email, however, there’s one major red flag about this application. The applicant is not talking anything about the startup he is applying to and how he will benefit them. This shows that the applicant has not researched about the company's business and engineering. So, how to write an application email for Software Engineering Internships at startups?

Find the right point of contact

Try to address the right person in the company. When you begin with “Hi” or “Hey there” or “Sir/Ma’am” you’re diffusing the responsibility of a reply, a lot of emails are lost in the haystack because everybody in the group thinks that it is not meant for them or someone else will reply. Connect with someone in the company and ask them for the right person to contact for the purpose. Address them in your application email.

Keep the intro short

Keep the subject line and introduction short. Begin with your name, major and institute. That’d be all. Next you should be talking about what you know about the company and how you both can benefit each other.

Talk more about what you can give to the company, less about what you’ll take away

Research about the company’s engineering. Many tech companies have engineering blogs. You’ll know what technologies they use. Now you have what technologies you should highlight in the application, only if you know them well.
Check out the open source projects of the company. Every good tech company knows what engineering tasks they are going to accomplish in the upcoming year. You can contribute to their public repositories. And then highlight this in your application.
Use the product or services offered by the company. Find all sorts of possible improvements and suggest solutions for them in your application email. Every user out there is pointing out problems to them via support tickets, so suggesting solutions for them is an important part.

Sure that’s going to make your application a little longer than usual, however, it will make you stand out among the crowd. Ideally, such an application should be addressed to one of the engineers at the company.

Be objective about why you’d be a good addition to the team

Terms like “I’ll be a good addition to the team”, “Fast learner” etc. are subjective in nature. You have to prove it objectively. This is why many companies have started giving away take-home projects. Candidates can work on it for a week and depending on the work accomplished, companies get a good idea of how the candidate will perform during the internship. Some companies think that the candidate can cheat by asking someone else to do the take-home project. So they keep the candidate for a week-long project on trial. To overcome all of this, you, as a candidate, can think of features or apps that you can build which could be of value to the company. You can also make use of any APIs exposed by the company. You can then highlight such contributions to the company in your application, which shows that you’re reliable because you have a good past record.

Have an online presence

LinkedIn and AngelList are extensively used by Talent Acquisition team because they are quite familiar with their profile format and features. A Github account with few repositories and regular commits helps you in two ways: It shows that 1. You know how to use git 2. You’re consistent at work. Engineers may check your code to judge you by its quality.

You may also create a portfolio for yourself. You can extensively highlight all your projects in the portfolio. You can also write tech blog posts about challenges you faced during some project and how you solved them. By thy way, if you’re good at communication (written or verbal) you will do well in any job in the world. And your application email is one of the things by which every company is going to judge your communication skills.

Résumé

Lastly, prepare a short résumé that highlights your strengths and modify it for the target company. The resume format suggested by careercup seems adequate. However, it is suggested to apply your creativity to make it stand out. People don’t spend more than 30 seconds to go through any resume. Make sure you make those 30 seconds count.

All of the above points are “DOs”, let’s have a look at few of the “DON'Ts”:

Don’t send blind emails in bulk in `to` or `cc` or `bcc` expecting at least one of them to respond. Target few companies and write personalized emails.
Don’t write a subject line longer than 5-8 words.
Don’t share your email format with your friend who is going to send the same email to the company by replacing a few things. You both will be rejected.
Don’t mention all the technologies you know, a company is not interested in what you know, they are interested in what you know that they use. Do your research well.
Don’t include subjective statements which cannot be proved like “I always give my 100%” and similar statements.
Don’t send reminder emails on your application email frequently. Give it a week for them to respond. They receive hundreds of emails every day.
Don’t say that “Review my CV and match it to open roles in your company”. It is candidate’s duty to target a particular position.

The startup hiring process includes resume filtering, phone screening, face-to-face interviews (plus take-home projects in some cases) and final interview with founders. Many good candidates are not able to get past the first hurdle. To all those candidates, next time you apply for an internship, use this post as a checklist. All the best!Till next time. Evíva!

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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.

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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

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