Hey everyone!

I'm curious to know how you all approach revising DSA problems after solving them.

Do you follow a sprint-wise approach, revisit problems based on patterns/topics, maintain a revision tracker, or follow something like spaced repetition?

A few things I'd love to hear your thoughts on:

• How frequently do you revisit previously solved problems?
• Do you revise problems topic-wise or follow a fixed schedule?
• How do you decide which problems need more attention?
• Do you maintain notes or revisit the problem and solve it from scratch?

I'm trying to build a consistent and effective revision strategy, especially to retain problem-solving patterns and improve recall during interviews.

Would love to hear about your approaches, experiences, and any tips that have worked well for you!

Thanks in advance!

ServiceNow is looking for an experienced software engineer to work on enterprise-scale applications and collaboration platforms. The role involves building interactive applications, developing backend services, and improving the platform's performance and scalability.
Location: Hyderabad, India
Experience: 5+ years
Work Mode: Flexible

What You'll Work On

• Build highly interactive applications that can handle complex workloads.

• Develop tools, libraries, and frameworks for other engineers.

• Work on backend services and scalable user interfaces.

• Build new features and improve existing products.

• Write clean, reusable code and maintain quality through testing and code reviews.

• Work with product teams from requirement gathering to final delivery.

• Mentor team members and share technical knowledge.

Skills Required

• Bachelor's or Master's degree in Computer Science or a related field.

• 5+ years of software industry experience (for bachelor's degree holders).

• Strong experience with Java, JUnit, REST APIs, and JSON.

• Knowledge of relational databases, SQL, Spring, and Hibernate.

• Good understanding of JavaScript and frontend development.

• Experience designing high-volume, interactive applications.

• Strong understanding of software design, usability, and scalability.

• Good written and verbal communication skills.

Good to have:

• Python

• CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI.

• Docker, Kubernetes, and cloud platforms (AWS, Azure, or GCP).

• Microservices architecture.

• Monitoring and observability tools such as Grafana, Prometheus, or Splunk.

Apply: https://careers.servicenow.com/jobs/744000158459419/sr-software-engineer/

Moving from an SDET role to a backend engineering position at Microsoft is a significant career transition. I’ve received an offer for Software Engineer (Backend), L60, and wanted to share the compensation details to get feedback from others in the industry.

My profile

• Education: B.Tech, Tier 2 college

• Experience: 2.5 years

• Current role: SDET

Microsoft offer breakdown

• Role: Software Engineer (Backend), L60

• Location: Hyderabad

• Base salary: ₹22 LPA

• Joining bonus: ₹3.8 lakh in the first year and ₹3.8 lakh in the second year

• Stocks: $40,000 over 4 years, vested equally

• Performance bonus: 0-20% of base salary (average around 10%)

• Relocation: Not included; relocation expenses will be self-funded

Standard Microsoft benefits

• Health insurance and employee wellbeing programmes

• Flexible and hybrid working arrangements, depending on team requirements

• Paid time off and company holidays

• Parental and family-care leave

• Employee communities, networking, and mentoring programmes

• Employee discounts on Microsoft products and services

• Office facilities and other employee perks

I’m unsure whether this is a competitive offer for an L60 backend role with 2.5 years of experience or if there was room to negotiate a better package.

Would appreciate feedback from Microsoft employees and engineers familiar with L60 compensation, particularly regarding the base salary, stock grants, bonus structure, and benefits.

TransUnion is hiring an Associate Software Engineer for its TruAudience Marketing Solutions team. This is an entry-level full-stack role where you'll work on web applications, backend services, data processing, and AI-powered features.

It's suitable for fresh graduates and early-career engineers with a good foundation in programming and an interest in learning across different areas of software development.
Location: Bengaluru, India
Experience: 0-2 years
Work Mode: Hybrid (minimum 2 days a week in office)

What You'll Work On

• Build, test, and maintain web applications and backend services.

• Develop responsive frontend interfaces and scalable REST APIs.

• Work with Java-based services, microservices, and distributed systems.

• Contribute to data processing and analytics solutions.

• Explore AI-powered features such as intelligent search, chat, and recommendations.

• Work with product managers, designers, and engineers to deliver features.

• Improve application performance, testing, and deployment processes.

Skills Required

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

• 0–2 years of software engineering experience (projects, internships, or full-time work).

• Good understanding of DSA, OOP, and computer science fundamentals.

• Proficiency in at least one language: Java, JavaScript/TypeScript, or Python.

• Basic knowledge of HTML, CSS, REST APIs, and SQL.

• Understanding of client-server architecture.

• Good problem-solving and communication skills.

Good to have:

• React or Angular, TypeScript, and Spring Boot.

• Microservices and distributed systems.

• Apache Spark and data processing.

• Generative AI, LLMs, RAG, and prompt engineering.

• AWS or GCP, Docker, Kubernetes, Git, and CI/CD.

Apply here: https://transunion.wd5.myworkdayjobs.com/transunion/job/Bengaluru/Associate-Software-Engineer_19042895

What happens when a tech company changes the kind of engineers it wants to hire because of AI?

That's the conversation Proton has sparked.

According to reports, Proton plans to stop hiring engineers after 2026 and instead focus on recruiting people who can build products using AI. Its CEO believes engineers will increasingly guide AI, review its output, test solutions and focus on building better products.

• This reflects an interesting shift in software development. AI tools can already generate code, explain unfamiliar codebases, suggest fixes and help developers build features faster.

• But there's one thing worth remembering: AI can help write code, but strong engineering skills help you understand whether that code is actually correct.

This is where DSA, problem-solving and computer science fundamentals continue to play an important role.

Understanding data structures and algorithms helps engineers think about efficiency, break down complex problems and choose better solutions. Knowledge of operating systems, databases, networking and system design helps them build reliable applications.

AI can become a powerful addition to these skills, helping developers work faster, explore solutions and improve productivity.

For students preparing for software engineering roles, the opportunity is to build both:

- Develop strong DSA and problem-solving skills.

- Understand core computer science concepts.

- Learn to use AI tools effectively in real development workflows.

- Build projects where you can apply, test and improve your engineering decisions.

The future of software engineering isn't about choosing between DSA and AI. It's about combining strong fundamentals with the ability to use new tools effectively.

What do you think will make an engineer stand out in the coming years: strong problem-solving, AI-assisted development, or the ability to combine both?

Location: Hyderabad, India
Experience: 9+ years
Work Mode: Flexible

ServiceNow is looking for a Staff Software Engineer to join its engineering team in Hyderabad. The role involves building scalable software, contributing to product design, and taking ownership of engineering work from planning to delivery.

What You'll Work On

• Design and develop clean, scalable, and reusable software.

• Work with product teams to understand requirements and deliver features.

• Contribute to new products while improving existing ones.

• Build software that customers can easily extend and customise.

• Maintain code quality through testing, code reviews, and engineering best practices.

• Mentor teammates and encourage knowledge sharing.

• Manage projects involving significant technical challenges.

Skills Required

• 9+ years of experience with Java or a similar object-oriented language.

• Strong understanding of JavaScript and web technologies.

• Experience with modern frontend frameworks such as Angular, React, or Vue.

• Good knowledge of data structures, algorithms, OOP, and design patterns.

• Understanding of application performance and scalability.

• Strong analytical, software design, and problem-solving skills.

• Experience evaluating or using AI-powered tools and workflows.

Apply here: https://careers.servicenow.com/jobs/744000158457389/staff-software-engineer/

I was reading a security report today and thought I should share it with the community, as it directly impacts our daily development workflows and local setups.

If you regularly use AI coding assistants or extensions in VS Code or Cursor, this recent incident is a major wake-up call.

What Happened?

A maliciously modified version of Anthropic's Claude Code extension managed to slip onto Cursor's extension marketplace. It remained live for several hours and impacted up to 5,000 users.

According to statements regarding the incident, the compromised extension actively attempted to collect sensitive system information, including:

• Usernames and Hostnames

• Operating System details

• Public IP addresses

• Attempts to establish remote access to the host machine

As developers, AI tools have quickly become an essential part of how we write code. However, this situation highlights a crucial aspect of software engineering: security doesn't stop at the code we write, it extends to the developer tools, extensions, and environments we trust.

When we grant AI agents direct access to our terminals, local codebases, and environment variables, the potential blast radius of a compromised extension expands significantly. Here are a few essential habits we should all adopt:

1. Verify Extension Publishers: Double-check publisher authenticity, download counts, and official badges before installing any tool.

2. Review System Permissions: Limit terminal execution privileges and inspect what local permissions a tool actually requires.

3. Audit Your Extensions Regularly: Keep your development tools updated, and immediately remove unused extensions or plugins.

4. Restrict Access to Sensitive Data: Be extremely careful about giving AI extensions access to secrets, API keys, .env files, or unrestricted terminal access.

Final Thought

AI tools can dramatically speed up our workflow, but using them responsibly is just as vital. Moving forward, before installing a shiny new extension, don't just ask: "Will this make me more productive?" Also ask: "Do I trust this tool in my environment?"

How do you handle security for your local development setup? Do you audit third-party extensions before installing them? Let's discuss in the comments below!

Preparing for an Amazon interview? Don't make the mistake of focusing only on DSA, system design, and technical fundamentals. There's another major component that candidates frequently underestimate: Behavioral Questions based on Amazon's Leadership Principles (LPs).

While prepping for my own technical rounds, I spent a lot of time researching how Amazon evaluates candidates. The biggest takeaway? Amazon doesn't just evaluate what you can build, they care deeply about how you approach problems, take ownership, handle failures, make decisions under uncertainty, and deliver results.

Simply memorizing the 16 Leadership Principles isn't going to cut it. You need real, structured experiences that prove you embody them. To help everyone currently in the prep loop, I compiled and structured this breakdown of 20 essential STAR stories/questions you should have ready in your toolkit before stepping into the interview.

First, Master the STAR Method

If you aren't using the STAR framework for behavioral responses, start now. It keeps your answers concise, structured, and impact-driven:

• S - Situation: Set the context and explain the specific challenge you faced.

• T - Task: Describe your actual responsibility or what outcome was expected.

• A - Action: Detail the precise steps you personally took to solve it. (Focus on "I", not just "we")

• R - Result: Share the quantifiable outcome, metrics, or key lessons learned.

20 STAR Stories You Should Prepare

Here are 20 core behavioral questions categorized by key Leadership Principles that I recommend mapping out ahead of time:

1. Ownership

• Question 1: Tell me about a time when you took responsibility for something that wasn't originally part of your role or scope.

• Question 2: Describe a situation where you identified an underlying issue and took ownership of fixing it without being asked.

2. Customer Obsession

• Question 3: Tell me about a time when you went beyond expectations to solve a critical issue for a user or customer.

• Question 4: Describe a situation where you made a key technical or product decision based directly on user feedback.

3. Bias for Action

• Question 5: Tell me about a time when you had to make an important decision quickly with limited or ambiguous information.

• Question 6: Describe a situation where taking immediate action helped prevent a much bigger problem down the line.

4. Dive Deep

• Question 7: Tell me about a time when you investigated a complex, edge-case bug or system failure to identify its root cause.

• Question 8: Describe a situation where deep data analysis changed your initial hypothesis or led to a better technical decision.

5. Deliver Results

• Question 9: Tell me about a challenging goal or project deadline you achieved despite facing significant obstacles.

• Question 10: Describe a time when you had to deliver a critical feature or fix under an extremely tight timeline.

6. Earn Trust

• Question 11: Tell me about a time when you had a technical disagreement with a teammate or cross-functional partner. How did you resolve it?

• Question 12: Describe a situation where you made a mistake or caused an outage, and how you communicated it to your team or manager.

7. Learn and Be Curious

• Question 13: Tell me about a time when you had to learn a completely new tech stack, framework, or domain from scratch to finish a task.

• Question 14: Describe a situation where you received constructive feedback and actively used it to improve your performance.

8. Invent and Simplify

• Question 15: Tell me about a time when you simplified a complex system architecture, legacy codebase, or manual workflow.

• Question 16: Describe a situation where you came up with an innovative technical solution to an existing bottleneck.

9. Have Backbone; Disagree and Commit

• Question 17: Tell me about a time when you strongly disagreed with your manager or team lead regarding a technical approach or architecture design.

• Question 18: Describe a situation where you advocated for your approach, but ultimately committed to a different path chosen by the team.

10. Insist on the Highest Standards

• Question 19: Tell me about a time when you identified a code quality, testing, or architecture flaw that others had overlooked.

• Question 20: Describe a situation where you proactively raised the engineering standards or test coverage for a project.

How to Build Your Story Bank Efficiently

• You don't need 20 completely unique, isolated stories. From my research and prep experience, 4 to 6 strong, multi-faceted experiences from your full-time work, internships, or major technical projects can usually cover all 20 questions.

• A single complex project scenario can easily flex to answer a Dive Deep, Customer Obsession, or Deliver Results question depending on which aspect of the story you emphasize.

Key Tips to Keep in Mind:

• Be Genuine & Specific: Don't invent fake metrics or exaggerated scenarios. Amazon interviewers are trained to drill down into the fine details during follow-ups.

• Highlight Your Direct Impact: Clearly separate what the team did from what you designed, debugged, or implemented.

• Quantify Everything You Can: Mention concrete numbers wherever possible, latency reductions, percentage gains in test coverage, query optimization speedups, or time saved.

• Don't Fear Failure Stories: Amazon loves stories about failed attempts or mistakes, provided you demonstrate accountability and clear lessons learned.

Okta is looking for a Senior Full Stack Engineer to join its ISV Ecosystem team. The team is building developer-focused products that help B2B SaaS applications connect with identity providers more easily.

The role involves working across backend APIs and frontend components, with a focus on building secure, scalable applications.
Location: Bengaluru, India
Experience: 4-6 years

What You'll Work On

• Build reusable UI components and developer-friendly APIs and SDKs.

• Develop frontend features using React.

• Build backend services using Node.js, TypeScript, and JavaScript.

• Work with product managers, designers, and architects to plan and deliver features.

• Improve application security, performance, reliability, and observability.

• Participate in design reviews, code reviews, and test-driven development.

Skills Required

• 4-6 years of software development experience.

• Strong experience with Node.js, TypeScript, and JavaScript.

• Hands-on experience building UI components using React.

• Good understanding of asynchronous programming and HTTP fundamentals.

• Experience with API design and at least one database: MySQL, Redis, or PostgreSQL.

• Experience with cloud platforms such as AWS, GCP, or Azure.

• Understanding of distributed systems concepts like caching and asynchronous processing.

• Strong ownership, problem-solving, and communication skills.

Good to have: Knowledge of OAuth, OIDC, SAML, and application security.

Apply here: https://www.okta.com/company/careers/rd/senior-software-engineer-full-stack-8317731/

Location: Bengaluru, India
Work Mode: Onsite

Hewlett Packard Enterprise (HPE) is looking for a Systems/Software Engineer I to work in its lab engineering team.

The role involves handling lab infrastructure, troubleshooting hardware and network issues, setting up devices, and working with virtual machines. It's a good opportunity for someone interested in Linux/Unix systems and networking.

What You'll Work On

• Install and configure network and computer equipment.

• Reinstall software on lab devices and add new devices to internal databases.

• Troubleshoot and replace faulty hardware.

• Configure and maintain network topologies between devices.

• Build and deploy virtual machines using VMware ESX vCenter.

• Resolve lab support tickets and help maintain a safe, organised lab environment.

• Guide and support junior lab administrators.

Skills Required

• Hands-on experience with Linux/Unix configuration.

• Understanding of networking and UNIX concepts.

• Ability to configure and troubleshoot JUNOS-based routers.

• Interest in expanding knowledge of networking and router technologies.

• Willingness to pursue Juniper certification.

Apply here: https://hpe.wd5.myworkdayjobs.com/Jobsathpe/job/Bengaluru-Karnataka-India/Lab-Engineer-I_1216116-2

Coming from a non-CS background and preparing for software engineering interviews can feel challenging.

Whether you studied Mechanical, Electrical, Civil, Chemical, Physics, or another discipline, you might have faced questions like:

• Why did you choose software development after studying a different field?

• What made you switch to tech?

• Do you have the same fundamentals as CS graduates?

• Why should we hire you over someone with a CS degree?

Sometimes, the challenge isn't your technical knowledge. It's explaining your journey in a way that makes the interviewer confident about your decision and abilities.

The good news is that you don't need to apologise for having a non-CS background. You need to show how you've built the skills required for the role.

Here is how you can approach these questions in interviews.

1. Have a Clear Reason for Choosing Software Development

When an interviewer asks why you moved into tech, avoid giving generic answers like "I have always been interested in coding" unless you can genuinely explain them.

Talk about what sparked your interest.

Maybe you started learning programming during college, enjoyed solving logical problems, built your first project, or discovered that you wanted to pursue software development professionally.

Keep your explanation honest and connect it to the steps you took afterwards.

2. Don't Make Your Degree Sound Like a Disadvantage

Avoid statements like:

"I am from a non-CS background, so I don't have as much knowledge as CS students."

This immediately shifts the conversation towards what you lack.

Instead, acknowledge your academic background confidently and focus on the technical skills you've developed.

For example:

"I completed my degree in Mechanical Engineering, but during college, I developed an interest in programming and started learning software development. Over time, I worked on projects, practised DSA, and studied core computer science concepts to prepare for software engineering roles."

Your degree is part of your journey, not a limitation you need to defend.

3. Demonstrate Your Technical Preparation

Your explanation becomes much stronger when you can support it with actual work.

Be prepared to discuss:

• DSA: Your problem-solving approach, coding practice, and understanding of common patterns.

• Core CS Subjects: DBMS, Operating Systems, Computer Networks, and OOP concepts.

• Projects: What you built, which technologies you used, and the technical decisions you made.

• Programming Languages: Your proficiency in the languages relevant to the role.

Don't just mention that you've studied these topics. Be ready to answer follow-up questions and explain your understanding.

4. Connect Your Previous Background to Your New Career

Your previous degree may have helped you develop skills that are also useful in software engineering.

For example, an engineering or science background might have exposed you to analytical thinking, structured problem-solving, teamwork, or working on complex problems.

You don't need to force a connection between your branch and software development. Just identify genuine experiences that demonstrate transferable skills.

5. Prepare for the Follow-Up Questions

Interviewers may want to understand whether your decision to enter tech is well thought out.

Some common follow-up questions include:

• Why didn't you pursue a career in your original academic field?

• How did you learn programming without a CS curriculum?

• How do you keep yourself updated with new technologies?

• What was the most challenging part of transitioning into software development?

• How do you ensure your CS fundamentals are strong?

Prepare honest, specific answers rather than memorising scripted responses.

If you're wondering whether it's possible to enter the tech industry without a traditional CS degree, consider the journey of Rohan Pattanayak.

Rohan pursued an M.Sc. in Physics from IIT Hyderabad and eventually secured an opportunity at TCS Research & Innovation.

His story is a good reminder that your academic branch doesn't have to define your career path.

Read his complete journey here:
https://takeuforward.org/community/success-stories/from-an-msc-in-physics-to-tcs-research

Switching from a non-CS background to software development comes with its own challenges, but it also teaches you how to learn independently and adapt to unfamiliar subjects.

If you're from a non-CS background, don't let the first question about your degree make you uncomfortable. Own your journey and be ready to explain the effort behind it.

Working a 9-5 while trying to prep for a job switch is honestly exhausting. After spending 8-9 hours dealing with work deadlines, meetings, and daily responsibilities, finding the energy to sit down and study DSA or revise core CS subjects can feel like taking on a second job.

I’ve definitely been there, starting out with a ton of motivation, setting some unrealistic 5-6 hour daily study goal, and managing to stick with it for maybe three days before work gets hectic, fatigue sets in, and the whole routine falls apart.

What I’ve realized is that the secret isn’t trying to force yourself to study for longer hours. It’s about building a sustainable routine that actually fits alongside a full-time job. Here is what has been working for me:

Set Realistic Daily Goals

I've learned to stop expecting myself to study for 5 hours after a full day at the office. Instead, I aim for 1–2 focused hours on weekdays.

I also make sure I know what I'm doing before I sit down. Vague goals like "study DSA today" always lead to procrastination, so I try to set specific targets, like solving two array problems or revising binary search. Small, achievable wins make it way easier to stay consistent.

Make the Most of Weekends

Weekends are where I actually get deep-focus time. I use them for:

• Revising important DSA patterns and tackling medium-level problems.

• Studying core CS subjects like DBMS, OS, and Computer Networks.

• Working on personal projects and polishing up my resume.

• Taking mock interviews and getting used to timed coding assessments.

That said, I try not to turn every weekend into a total study marathon. Burning out on a Sunday means walking into Monday completely drained, which defeats the whole purpose.

Prioritise Instead of Trying to Learn Everything

When time is your biggest constraint, you simply cannot afford to study everything randomly.

I map out my target roles, check what companies actually look for in interviews, and focus strictly on those topics. For software engineering, that means doubling down on DSA, problem-solving, core fundamentals, and practical projects.

A focused strategy beats jumping between a dozen different resources every single time.

Use Small Time Slots During the Day

You don’t always need a dedicated two-hour block to move the needle. I’ve started utilizing weird pockets of time throughout the day:

• Reviewing flashcards or quick notes during a commute.

• Reading up on a CS concept during a quick work break.

• Mentally revisiting a tricky problem I was stuck on the previous evening.

These micro-sessions help keep the continuity going without eating into my personal downtime.

Don't Sacrifice Sleep and Health

Staying awake until 2-3 AM trying to grind out prep targets is a trap.

It might work for a couple of days, but eventually, it catches up to you, your focus drops, your work quality slips, and you end up exhausted everywhere. A well-rested mind actually retains concepts way faster anyway.

I try to protect my sleep, fit in some movement, and leave room for actual downtime.

Track Progress, Not Just Hours

Studying for two hours doesn't magically mean you've made progress. I've started focusing on what I actually accomplished:

• How many problems did I solve independently?

• Can I actually explain this concept out loud now?

• Am I faster than I was last month?

Reviewing this weekly helps me course-correct instead of just measuring time spent staring at a screen.

Balancing a full-time job and career prep is tough, but it's totally doable if you drop the perfectionism. You don't need to quit your job, study 6 hours a day, or give up your social life. You just need a realistic plan, patience, and consistency.

For anyone else out there juggling a 9-5 while prepping for a switch,

How are you managing your office work and interview prep together? What does your daily routine look like?

Getting rejected once is disappointing. Getting rejected multiple times, especially after putting in weeks or months of preparation, can make you question your skills, preparation, and even your decision to pursue a career in tech.

You might start wondering whether you're good enough, whether your preparation is going in the right direction, or whether everyone else is moving ahead while you're stuck.

But here's something worth remembering:

Multiple interview rejections don't mean you're not capable. They often mean there's still something to learn, improve, or approach differently.

1. Give Yourself Time to Process the Rejection

It's completely normal to feel disappointed after an interview rejection. Don't force yourself to immediately get back to studying or pretend that it doesn't affect you.

Take a little time to process what happened. Just make sure you don't let one rejection turn into days of self-doubt.

2. Stop Treating Every Rejection as a Personal Failure

An interview outcome depends on several factors, not just your technical knowledge. It could be the role's expectations, the interviewer's evaluation, communication, problem-solving approach, or even the competition.

Instead of thinking, "I'm not good enough," try asking, "What could I have done better?"

That small change in perspective can make a big difference.

3. Analyse Your Previous Interviews

Don't let the experience go to waste. Think about the questions you struggled with, the concepts you couldn't explain clearly, and the moments where you got stuck.

Identify whether the gaps were in DSA, core CS subjects, projects, problem-solving, or communication.

You don't need to prepare everything again. Focus on the areas that repeatedly create problems.

4. Fix Your Preparation Strategy

Sometimes, the issue isn't how much you're studying but how you're studying.

If you're solving problems but struggling to explain your approach, practise thinking aloud. If you're unable to solve unfamiliar questions, focus on understanding patterns instead of memorising solutions.

Also, revise important concepts regularly and take mock interviews to get comfortable with the actual interview environment.

5. Don't Compare Your Journey With Others

Seeing your friends get placed while you're facing repeated rejections can be frustrating.

But everyone's journey has a different timeline. Someone getting selected before you doesn't mean you're falling behind.

Focus on your own progress rather than constantly measuring it against someone else's success.

6. Keep Applying While Improving

Don't wait until you feel 100% prepared before applying again.

Continue exploring opportunities, appearing for interviews, and learning from each experience. Real interviews can teach you things that preparation alone sometimes cannot.

The goal isn't to avoid rejection completely. It's to become better prepared for the next opportunity.

One Thing to Remember

• Your last interview rejection is not a final verdict on your abilities.

• You can be a good problem solver and still struggle in an interview. You can prepare for months and still encounter questions you haven't seen before.

• What matters is whether you take something valuable from each experience and use it to improve.

Don't let multiple rejections convince you to give up on something you've worked so hard for. Take a break if you need one, rethink your approach, work on your gaps, and give yourself another chance.

Sometimes, the opportunity you're waiting for comes after a few interviews that didn't go your way.

To everyone who has faced multiple interview rejections, What helped you regain confidence and get back on track?

Landing an internship with a performance-based PPO opportunity is an exciting milestone, and I’m happy to share my selection at Rippling through the on-campus placement drive.

Offer Details

• Company: Rippling

• Role: SDE Intern + Performance-Based PPO

• College: Tier 2

• Location: Bengaluru

• Internship stipend: ₹1 lakh per month

• Full-time CTC: ₹44 LPA

• Base salary: ₹36 LPA

• Other components: ₹8 LPA

• Result: Selected

Iris Software is looking for a Senior Engineer to work on enterprise GenAI solutions. The role involves building AI agents, working on RAG-based applications, and connecting AI systems with enterprise platforms and services.

If you've been working with LLMs and want to build AI solutions beyond basic chatbots, this role is worth checking out.
Location: Noida, Uttar Pradesh

What You'll Work On

• Build GenAI applications using Azure OpenAI, Azure AI Foundry, and other AI platforms.

• Develop RAG and Graph RAG solutions for enterprise use cases.

• Build AI agents that can use tools, handle tasks, and work with other agents.

• Work with LangChain and LangGraph to build and manage AI workflows.

• Integrate vector databases, semantic search, APIs, and enterprise data sources.

• Improve prompts, retrieval quality, and AI response accuracy.

• Work on model fine-tuning and customization where needed.

• Build evaluation systems to check the quality and reliability of AI responses.

• Implement Human-in-the-Loop workflows and follow responsible AI practices.

• Help troubleshoot complex AI issues and guide team members on GenAI development.

Skills They're Looking For

• RAG and advanced GenAI concepts.

• Agentic AI systems, tool calling, and multi-agent workflows.

• Azure AI Foundry and Azure OpenAI Service.

• LangChain and AI workflow development.

• Cloud application integration and deployment.

Good to Know: Experience with LangGraph, AutoGen, CrewAI, Graph RAG, and vector databases is relevant to the work described in this role.

Apply here:
https://careers.irissoftware.com/job/Noida-Azure-AI-Platform-Senior-Engineer-UP/60264244/

Moving from a startup to a larger organisation like ANZ feels like an interesting next step, especially with the opportunity to work in the institutional banking domain. I’ve accepted the offer and am sharing the compensation details for others exploring similar roles.

My profile

• Education: B.Tech, Tier 3 college (ENTC)

• Experience: 3.4 years

• Current company: Startup

• Current CTC: ₹22.5 LPA

ANZ offer breakdown

• Role: Engineer 4

• Location: Bengaluru

• Base salary: ₹28 LPA

• Annual bonus: 5% of base salary

• Joining bonus: None

• RSUs: None

• Allowances: ₹3 LPA

• Estimated first-year TC, including PF: Approximately ₹33 LPA

Additional benefits

• Cab facility

• Meals

• Gym services

The compensation is a step up from my current package, but what also stood out to me was the overall work environment and the opportunity to gain experience in institutional banking technology.

I’m sharing this breakdown to help others preparing for similar roles benchmark their offers and understand the compensation and benefits ANZ provides at this experience level.