Required Skills & Tech Stack
Python
JavaScript
Java
C#
SQL
NoSQL
REST APIs
Prompt Engineering
Large Language Model Integration
AI Output Validation
Git
Agile/Scrum
CI/CD
Problem Solving
Communication
📚 Free Study Materials (4)
📖
Aptitude Practice Questions
Open Resource ↗
Helps candidates sharpen quantitative and logical reasoning skills required for the online assessment at Marsh.
📖
Technical Interview Preparation Guide
Open Resource ↗
Provides coding patterns, data‑structure concepts and interview tips useful for Marsh’s technical interview round.
📖
Comprehensive Interview Resources
Open Resource ↗
Covers behavioral questions, resume building, and mock interview strategies to ace the HR round at Marsh.
📖
Coding Practice Platform
Open Resource ↗
Offers a wide range of algorithmic problems to practice coding efficiency and problem‑solving for Marsh’s technical test.
Eligibility Criteria
• B.E./B.Tech in Computer Science, Information Technology or a related engineering discipline. • Expected graduation year: 2027. • Minimum 60% aggregate in academic records. • No active backlogs in any subject. • Hands‑on programming experience in at least one modern language (Python, JavaScript, Java, C#). • Understanding of AI/ML and generative AI concepts. • Working knowledge of SQL and/or NoSQL databases. • Demonstrated practical AI project, prototype, workflow or use‑case beyond mere code generation. • Ability to work from the Pune office at least three days a week under a hybrid model. • Willingness to adapt to a 24×7 shift environment if required.
Selection & Interview Process
1
Round 1: Online assessment (aptitude + coding)
2
Round 2: Technical interview (programming, AI concepts, prompt engineering)
3
Round 3: HR interview (fit, motivation, availability)
Job Description & Key Responsibilities
Marsh is a leading global insurance broker and risk management firm with a strong presence in India. The company helps businesses navigate complex risk landscapes by offering innovative insurance solutions, advisory services, and employee benefits programs. With a culture that encourages curiosity, collaboration, and continuous learning, Marsh has built a reputation for nurturing talent and providing exposure to cutting‑edge technologies across its IT and business domains.
The AI Native Intern – Applications Development role is part of Marsh’s IT Application Development team in Pune. This internship is designed for engineering students graduating in 2027 who are passionate about software development, artificial intelligence, and building real‑world AI‑enabled solutions. Unlike a traditional coding internship, this position focuses on responsible AI adoption, prompt engineering, validation of AI‑generated outputs, and security awareness. Interns will work closely with cross‑functional teams to design, develop, test, integrate, and support AI‑powered applications that drive value for Marsh’s Insurance Broking and Employee Benefits businesses.
Key Responsibilities:
1. Collaborate with product, data, and business teams to understand use‑cases and translate them into AI‑enabled solutions.
2. Develop, test, and maintain application code using Python, JavaScript or Java, adhering to coding standards.
3. Design and refine prompts for large language models (LLMs) to generate accurate and context‑aware outputs.
4. Integrate LLM APIs (e.g., OpenAI, Claude, Gemini) into applications and workflows.
5. Validate AI‑generated code and content for correctness, security, privacy, and performance.
6. Perform unit, integration, and functional testing of AI‑augmented features.
7. Document design decisions, validation approaches, and guardrails for AI usage.
8. Participate in Agile ceremonies, code reviews, and DevOps pipelines.
9. Support production monitoring, troubleshooting, and continuous improvement of AI services.
10. Contribute ideas for process automation and business‑process enhancements using AI.
Tech Stack: Python, JavaScript/Node.js, Java, SQL/NoSQL databases, RESTful APIs, Git, CI/CD tools, LLM platforms (OpenAI, Claude, Gemini), Agile/Scrum.
Growth Path: Successful interns may receive full‑time offers as Software Engineers, AI Engineers, or Product Developers, with opportunities to specialize in AI/ML, cloud platforms, or enterprise solutions. Marsh’s global network provides mentorship, certifications, and exposure to large‑scale projects.
Why Join Marsh: Interns gain hands‑on experience with emerging AI technologies in a regulated industry, learn responsible AI practices, and work alongside seasoned professionals. The hybrid model offers a balanced office‑home experience, and the company’s emphasis on learning, diversity, and employee well‑being makes it an attractive launchpad for a tech career.
Preparation Hub
Marsh — Data Analytics & SQL Interview Guide
Previously asked questions, exam syllabus, coding benchmarks & round strategy.
📖 Previously Asked Questions & Preparation Links
APTITUDE & LOGIC
📖
Aptitude Practice Questions & Online Mock Tests
Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.
Open Resource ↗
COMPANY GUIDE
🎯
Marsh Interview Preparation Corner
Comprehensive guide covering typical interview formats, common questions, and preparation tips for Marsh and off-campus tech roles.
Open Resource ↗
MOCK TESTS & PAPERS
📝
Comprehensive Interview Prep Resources & Syllabus
Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.
Open Resource ↗
CODING PRACTICE
💻
Algorithm and Data Structure Problem Set
Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.
Open Resource ↗
💻 Previously Asked Coding Challenges
Easy / Medium
⚡ Live Debugger
Two Sum & Two Pointers Array Optimization
Asked in 85% tech rounds
Medium
⚡ Live Debugger
Reverse Linked List & Detect Cycle (Floyd's Algorithm)
Frequently asked in core rounds
Medium
⚡ Live Debugger
SQL Nth Highest Salary with DENSE_RANK() & Subqueries
Top standard database question
Easy / Medium
⚡ Live Debugger
Valid Parentheses & Stack Implementation
Standard online assessment problem
🗺️ Round-Wise Strategy
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (Python, JavaScript, Java, C#, SQL, NoSQL, REST APIs, Prompt Engineering, Large Language Model Integration, AI Output Validation, Git, Agile/Scrum, CI/CD, Problem Solving, Communication) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
Marsh Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
❓ Core Technical Questions & Answers
What is the difference between WHERE and HAVING clauses in SQL? Answer ▼
Model Answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer ▼
Model Answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer ▼
Model Answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer ▼
Model Answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer ▼
Model Answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
🤝 Behavioral & HR Questions (STAR Method)
Why do you want to join Marsh as a Interns – Applications Development?
Preparation Tip: Highlight Marsh's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
