Most Demanding Entry Level Software Jobs in India for 2026

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Quick snapshot

1. Top roles to target for 2026

2. AI and machine learning engineer including prompt and model deployment roles

3. Cloud native engineer and site reliability engineer

4. Full stack and backend engineer for product companies and startups

5. Data engineer and analytics engineer

6. Cybersecurity analyst and application security engineer

7. Why these matter now

8. Companies are building real product features with models and data

9. Cloud infrastructure needs people who can run and automate systems at scale

10. Product based teams keep hiring for feature work and core services

11. Business teams want reliable data pipelines for analytics and machine learning

12. Security is now a default requirement for product and compliance

How to use this post

1. Read role descriptions and pick one or two to focus on

2. Follow the resources and links to build practical projects

3. Use the 12 week plan at the end to convert learning into a portfolio

How employers think about entry level hires

1. They want people who can reduce ramp up time

2. Projects that are deployed or clearly demonstrated matter more than certificates

3. Specialised skills in cloud, machine learning infra, or security usually attract a premium

4. Clear communication and a short write up for each project helps recruiters decide quickly

Role deep dives with what to build and where to apply

AI and machine learning engineer

What companies expect from fresh graduates

1. Ability to prototype models in Python

2. Familiarity with transformers and basic fine tuning

3. Understanding of model evaluation and bias

4. Basic knowledge of serving models behind an API

What to build and show

1. Small fine tuning project with a public dataset and a one page explanation

2. An inference API using FastAPI or Flask with a short demo video

Where to learn and resources

1. Practical courses on Coursera at https://www.coursera.org

2. Model hub and examples at https://huggingface.co

3. Coding practice at https://leetcode.com

4. Community notebooks and datasets at https://kaggle.com

Cloud native engineer and site reliability engineer

What companies expect from fresh graduates

1. Comfortable working with Linux and shell scripting

2. Basic container skills with Docker and Kubernetes concepts

3. Ability to create a simple CI pipeline and automate deployments

4. Understanding of infrastructure as code basics

What to build and show

1. Containerise a simple app and run it in a local Kubernetes cluster

2. Create a GitHub Actions pipeline that builds and deploys the app

3. Document a postmortem style note explaining a deployment issue and fix

Where to learn and resources

1. Docker documentation at https://www.docker.com

2. Kubernetes basics at https://kubernetes.io

3. Terraform guides at https://www.terraform.io

4. Practice pipelines with GitHub Actions at https://github.com

Full stack and backend engineer

What companies expect from fresh graduates

1. Strong programming skills in at least one language such as Java Python or Node.js

2. Good understanding of REST APIs databases and basic system design

3. Front end competence for full stack roles with React or similar frameworks

4. Test writing and code quality awareness

What to build and show

1. An end to end app with a front end a backend and a persistent database

2. A short write up about the architecture and trade offs you made

Where to learn and resources

1. Free project ideas and tutorials at https://github.com

2. Front end basics at https://reactjs.org

3. Backend patterns and guides at https://nodejs.org and https://www.python.org

Data engineer and analytics engineer

What companies expect from fresh graduates

1. SQL mastery including window functions and joins

2. Experience building simple ETL pipelines and scheduling jobs

3. Familiarity with parquet and columnar formats and partitioning strategies

4. Basic Spark or cloud data service knowledge

What to build and show

1. An ETL pipeline that ingests raw CSV transforms data and writes parquet files

2. An Airflow like DAG that runs the pipeline on a schedule

Where to learn and resources

1. SQL practice at https://mode.com or https://www.w3schools.com/sql

2. Apache Airflow at https://airflow.apache.org

3. Spark documentation at https://spark.apache.org

Cybersecurity analyst and application security

What companies expect from fresh graduates

1. Awareness of OWASP top ten vulnerabilities and secure coding basics

2. Ability to do simple vulnerability triage and reproduce issues safely

3. Familiarity with Linux networking and common security tools

What to build and show

1. A write up of a safe lab exercise using OWASP Juice Shop with steps and findings

2. A short script that automates a simple scan and produces a report

Where to learn and resources

1. OWASP materials at https://owasp.org

2. Practical labs and challenges at https://tryhackme.com and https://www.hackthebox.eu

Resume and portfolio checklist for fresh graduates

1. Two to three polished projects hosted on GitHub or a similar repo

2. One page README for each project that explains problem architecture and results

3. Short demo video or hosted live demo if possible

4. A single page resume tailored for the role with measurable impact statements

5. A short link to a portfolio or a single PDF that recruiters can open quickly

Interview preparation checklist

1. Practice coding daily on platforms like LeetCode at least one hour on focused topic days

2. Prepare one system design story about a project you built and be ready to sketch it on a whiteboard

3. Create a folder of short behavioral stories using the format Situation Action Result

4. Mock interviews with peers or on platforms that offer live practice

A simple 12 week plan to go from zero to interview ready

Week 1 to Week 4 focus on fundamentals

1. Pick one role to specialise in and pick one stack for that role

2. Spend three weeks on core skills for that role and one week building a small project

3. Post the code on GitHub add a clear README and a short demo clip

Week 5 to Week 8 build depth and polish

1. Expand the project into a deployable demo or add a production like component

2. Start practicing coding questions two to three times a week

3. Reach out to alumni or people on LinkedIn and ask for feedback and referrals

Week 9 to Week 12 interview focus and apply

1. Run mock interviews and refine your one pager for projects

2. Apply to roles with a tailored resume and a short cover note that links to the project

3. Keep learning from interview feedback and iterate on gaps quickly

Helpful links at a glance

1. LeetCode for coding practice https://leetcode.com

2. GitHub for project hosting https://github.com

3. Coursera for guided courses https://www.coursera.org

4. Hugging Face for models and examples https://huggingface.co

5. Docker documentation https://www.docker.com

6. Kubernetes documentation https://kubernetes.io

7. Terraform guides https://www.terraform.io

8. Apache Airflow https://airflow.apache.org

9. OWASP resources https://owasp.org

10. TryHackMe for security labs https://tryhackme.com

11. Kaggle for datasets and community notebooks https://kaggle.com

12. Internshala for early hiring and internships https://internshala.com

13. LinkedIn jobs to find openings https://www.linkedin.com/jobs

14. Indeed jobs to find openings https://www.indeed.com