Dev Opportunity Radar #14: MLH Global Hack Week, $40K Agents for Humans Hackathon & Razorpay AI Buildathon

TL;DR

Welcome back to Dev Opportunity Radar.

This is a weekly series where I share opportunities, resources, communities, and interesting finds that I come across, with the goal of helping people discover things they might otherwise miss.

This week's edition features the Razorpay AI Buildathon, Agents for Humans Hackathon, and MLH Global Hack Week: Data, along with Andrej Karpathy's Deep Dive into LLMs like ChatGPT as a resource worth checking out.

If you're new to the series, you can also browse previous editions, search past opportunities, and explore Community Finds, Reader Updates, and Resources Worth Checking Out on the Dev Opportunity Radar website. I've also written a short post about why I built it. You'll find links to both at the end of this article.

If you've discovered something through the radar, I'd love to hear about it. Whether you applied to an opportunity, joined a community, completed a program, or found a resource you hadn't seen before, I'd be happy to feature your experience in a future 💙 Reader Updates section (with your permission).

And if you've come across an opportunity, resource, community, program, or event that deserves more attention, feel free to share it in the comments.

If I feature one of your Community Finds in a future edition, I'll always make sure to credit you. If you discovered it, that recognition belongs to you.

Table of Contents

• ⚡ Quick Scan
• 🔄 Still Open From Previous Editions
• 📍 This Week's Opportunities
  • 📌 Razorpay AI Buildathon
  • 📌 Agents for Humans Hackathon
  • 📌 MLH Global Hack Week: Data
• 📚 Resources Worth Checking Out
  • Deep Dive into LLMs like ChatGPT
• 🌟 Community Finds
• 💙 Reader Updates
• 👋 Until Next Friday
• 🌐 Dev Opportunity Radar Website

⚡ Quick Scan

Opportunities

Agents for Humans Hackathon: Open internationally, but some countries and territories are excluded. Check the full eligibility rules before participating.

Resource Highlight

📝 A quick note: I spend a lot of time researching and verifying every opportunity before featuring it in Dev Opportunity Radar. However, deadlines, eligibility, program details, and application requirements can change after publication. Before applying, please take a few minutes to visit the official program page, review the latest information, and confirm that you're eligible.

🔄 Still Open From Previous Editions

Before we get into this week's opportunities, here are a few from the previous two editions that are still accepting applications.

Since this is already Edition #14, the list of opportunities covered across the earlier editions is starting to get quite long. I used to keep all the still-open opportunities here, but I don't think repeating the full list every week makes the editions easier to read.

So from this edition onward, I'll keep this section to the two most recent editions. This way, you can still get a quick reminder about recent opportunities without making the weekly edition too long.

If you're looking for opportunities from earlier editions, they're still available on the Dev Opportunity Radar website, where you can browse the full list and use the filters to find what you're looking for.

I've already covered the opportunities below in detail, so I won't repeat everything here. If any of them catch your attention, you can find the full overview, eligibility details, and application links in the original edition.

📍 This Week's Opportunities

Here are a few opportunities I came across this week that I thought were worth sharing.

📌 Razorpay AI Buildathon

Who it's for: Students interested in AI and software engineering who are able to work in person in Bangalore from September 2026.

What stands out: The Razorpay AI Buildathon is a student-only program where you build an AI project and use that project to apply for a 6 or 12-month AI Builder Internship at Razorpay.

There are five tracks you can choose from: AI Growth & Agentic Commerce, AI Risk Manager, AI Revenue Recovery, AI Finance Controller, and an Open Track if you want to build something outside the listed ideas.

I wanted to include this because I don't come across many opportunities where the project you build is actually part of the hiring process. Here, Razorpay is looking at how you think, what you build, how well it works, and even how you deal with things when they break.

Another thing I liked is that they don't make the application all about your resume. You'll need to submit a public GitHub repository, a five-minute pitch video, explain what your project solves, and talk about what broke and how you fixed it. There is also no aptitude test or group discussion. Shortlisted builders go directly to a panel.

The internship itself is also quite substantial. Selected students can choose between 6 or 12 months and receive a ₹75,000 monthly stipend while working in person in Bangalore.

I know many people reading the radar are looking for opportunities that are accessible globally, so this one is definitely more location-specific. I'm still sharing it because I think the combination of building something real + getting evaluated on your work + potentially turning that into a paid AI engineering internship makes this worth knowing about, especially for students in India who can be in Bangalore.

Internship: 6 or 12 months | Stipend: ₹75,000/month

Format: In person, Bangalore

Application Deadline: September 5, 2026

Application Requirements: Resume, project details, public GitHub repository, five-minute pitch video, and application questions.

🔗 Learn More & Apply

📌 Agents for Humans Hackathon

Who it's for: Developers, students, and builders who want to build an AI agent that can handle repetitive tasks for people. You can participate solo or with a team, and the hackathon is open to participants from around the world, with some countries and territories excluded.

What stands out: The Agents for Humans Hackathon, organized by AWS, is a six-week online hackathon where you build a new AI agent using the Strands Agents SDK. The idea is pretty simple: build something that can take care of a real task that people normally have to do themselves.

There are three tracks to choose from: Everyday Agents, for things like home, money, errands, or family tasks; Professional Agents, for repetitive work tasks; and Good Neighbor Agents, for agents that help groups such as nonprofits, schools, libraries, or local organizations.

I wanted to include this because I think the theme leaves quite a lot of room to build something you would actually want to use. You're not given one specific problem to solve, so you can start with a repetitive task you've personally dealt with and think about whether an agent could handle it.

Another thing I like is that the submission isn't just about showing an idea. You need to build a working agent, make your code publicly available, include an architecture diagram, and record a short demo showing it working. So if you're looking for a project that can also become something useful for your portfolio, this could be an interesting one to try.

The hackathon also provides $50 in AWS credits to help with build costs, and there is a total of $40,000 in cash prizes across the three tracks.

Prize Pool: $40,000

Format: Online | Build Period: Six weeks

Submission Deadline: September 15, 2026

Team Size: Solo or teams

What you need to build: A new AI agent using the Strands Agents SDK that handles a real, repetitive task.

Tracks: Everyday Agents, Professional Agents, and Good Neighbor Agents.

Additional Support: $50 in AWS credits are available for the build.

🔗 Learn More & Join the Hackathon

📌 MLH Global Hack Week: Data

Who it's for: Students, developers, and anyone interested in learning more about data, whether you're just getting started or already have some experience.

What stands out: Global Hack Week: Data is a free, week-long online event from Major League Hacking (MLH) where you can learn, build projects, complete challenges, and meet other people from the MLH community.

The week includes live workshops and technical challenges covering topics like SQL, databases, and data visualization. There are also smaller community events on Discord where you can meet other participants, work together, and take a break between challenges.

I wanted to include this because sometimes learning data skills can feel like you need to take a full course before you can actually start building something. This is a more relaxed way to spend a week exploring the area, learning something new, and actually putting it into practice.

Another thing I like is that you don't have to complete every challenge or already know what you're doing. Some challenges are simple, like connecting with other members of the community, while others involve building projects and creating demos. You can choose what you want to take on depending on your interests and experience.

And this one is actually global. It's completely free and open to participants from anywhere in the world, which is always something I look for when going through opportunities for the radar.

Event: September 11–17, 2026

Format: Fully online | Cost: Free

Topics: SQL, databases, data visualization, and other data-related technical skills.

🔗 Learn More & Register

📚 Resources Worth Checking Out

Not every useful find comes with an application deadline.

Here's one resource worth checking out this week.

Deep Dive into LLMs like ChatGPT

Who it's for: Developers, students, AI enthusiasts, and anyone who wants to understand how large language models like ChatGPT actually work. You don't need to be an AI researcher to follow it, but some basic technical knowledge will make it easier to get through the deeper sections.

What stands out: This is a free 3+ hour deep dive into LLMs by Andrej Karpathy, covering much more than just how to use ChatGPT. He walks through the full training stack, starting with internet data and tokenization, then moving into neural network internals, inference, pretraining, post-training, hallucinations, tool use, reinforcement learning, and how models actually "think."

I wanted to include this because there are so many resources about using AI tools, but fewer that actually help you understand what's happening underneath. If you've ever wondered how a large language model goes from a huge amount of text to something that can answer questions, write code, or use tools, this is a really good place to start.

Another thing I liked is that Karpathy doesn't only explain the technical side. He also talks about some of the strange ways LLMs behave, including hallucinations, tokenization problems, "jagged intelligence," knowledge and working memory, and why models can be surprisingly good at some things while struggling with others. That makes the video useful even if you're more interested in building with AI than training models yourself.

Format: Free recorded video | Length: Approximately 3 hours 22 minutes

Level: Beginner to Advanced

Topics Covered: LLM pretraining, tokenization, neural networks, inference, post-training, hallucinations, tool use, reinforcement learning, RLHF, DeepSeek-R1, and practical use of LLMs.

🔗 Watch the Video

🌟 Community Finds

One of my favorite things about this series has been seeing people share opportunities, communities, and resources that others might not have discovered otherwise.

We've had some really wonderful community finds over the last few weeks, and I honestly can't thank everyone enough for taking the time to find these opportunities, look through them, and send them my way. I know that takes time, and I appreciate every person who thinks of the Radar when they come across something they feel others might find useful 💙

This week, we weren't able to include a community find, but that's completely okay. Hopefully we'll have more wonderful finds from the community as we keep going.

So if you come across an opportunity, fellowship, grant, hackathon, conference, community, resource, or anything else you think more people should know about, please do send it my way. I love seeing what you find, and it helps make this series better for everyone.

If I feature something you shared in a future edition, I'll always make sure to credit you. If you discovered it, that recognition belongs to you.

One small request: If you're sharing an opportunity, please avoid posting raw URLs directly in the comments. DEV sometimes filters them before I get a chance to see them.

A short description alongside the link makes it much easier for me to review and potentially feature it in a future edition.

💙 Reader Updates

I'm looking forward to this section gradually growing over time, and I'd still love to hear from you.

One of my favorite parts of writing Dev Opportunity Radar has been hearing from people who discovered something they otherwise might have missed.

If you discovered an opportunity through the radar, applied to something, joined a community, attended an event, or simply found a resource you hadn't seen before, I'd genuinely love to hear about it.

You don't need to have been accepted or have a big success story to share. Sometimes simply discovering the right opportunity at the right time is already a win.

If you'd like to share an update, feel free to leave a comment on this edition. With your permission, I may feature it in a future 💙 Reader Updates section and tag you so other readers can celebrate your journey too.

I hope this section gradually becomes a place where we can celebrate those stories together, one update at a time.

👋 Until Next Friday

Before I go, I just want to say thank you.

Every week, I spend time searching for opportunities, resources, and communities that I think deserve a little more attention. But one of my favorite parts of this series isn't the research. It's seeing what happens after an edition is published.

Seeing someone discover an opportunity, apply to a program, share a resource, suggest a Community Find, or come back to tell us what they learned reminds me why I started Dev Opportunity Radar in the first place.

The goal has always been simple:

Help people discover opportunities they otherwise might have missed.

Thanks to all of you, it feels like we're doing exactly that.

Whether you've been reading since the very first edition or this is your first time here, thank you for being part of the journey. Every comment, suggestion, and shared opportunity helps make this series better than I could build on my own.

If you ever come across an opportunity, resource, event, community, or anything else you think deserves more attention, I'd love for you to share it in the comments. And if Dev Opportunity Radar helped you discover something exciting, I'd love to hear that too.

Thank you for reading, for sharing, and for helping make this our radar, not just mine.

I'll be back next Friday with more opportunities, resources, and Community Finds.

Until then, take care, and I hope you discover something amazing this week 💙

🌐 Dev Opportunity Radar Website

If this is your first time discovering the series, you can explore every edition, browse opportunities by category, discover Community Finds, and catch up on Reader Updates on the Dev Opportunity Radar website.

👉 Website

I also wrote a short post about why I built the website and the journey behind it.

👉 Website Launch Post