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REQUIREMENT_ID_1961 • 3-DAY_ACTIVE_POLICY JD

Full-Stack AI Intern

Company
Company Google
Type
Opportunity Type Internship
Salary
Stipend / Salary {'@type': 'QuantitativeValue', 'value': '', 'unitText': 'YEAR'}
Location
Location Bengaluru, Karnataka, India
Posted Date
Posted Date Yesterday
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React.js Python Node.js JavaScript TypeScript REST APIs LLMs Retrieval‑Augmented Generation LangGraph SQL ClickHouse Kafka YAML Git problem solving debugging
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Comprehensive Placement Papers Collection Open Resource ↗
Curated set of placement papers that help candidates practice quantitative and logical reasoning for Google recruitment.
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Recruitment Process Experiences Open Resource ↗
First‑hand accounts of candidates navigating Google's recruitment stages, useful for understanding interview flow at Google.
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Interview Preparation Guide Open Resource ↗
Structured guide covering topics, sample questions, and preparation tips for aspiring candidates targeting Google roles.
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Algorithm Problem Set Open Resource ↗
Extensive library of algorithmic problems to sharpen coding skills required for technical interviews at Google.

Eligible candidates must be pursuing a B.Tech, B.E, M.Tech, M.Sc or equivalent degree in Computer Science, Information Technology, Electronics & Communication, or related fields. Minimum CGPA/percentage of 6.5/70% (or equivalent) is required. Candidates from the graduating batches of 2023, 2024, 2025, or 2026 are welcome. No active backlogs are allowed at the time of joining. Strong programming fundamentals and a demonstrable interest in AI/ML or full‑stack development are essential.

1
Round 1: Online coding assessment
2
Round 2: Technical interview (focus on full‑stack and AI concepts)
3
Round 3: HR interview (fit and motivation)
GoComet is a fast‑growing technology company that is redefining global logistics through AI‑driven automation. Founded with the vision of making freight movement seamless, the firm combines deep domain expertise in supply chain with cutting‑edge machine learning, enabling shippers and carriers to make data‑backed decisions in real time. With a presence across major logistics hubs in India and a client base that spans continents, GoComet offers a vibrant environment where innovation meets real‑world impact. The organization invests heavily in research and development, fostering a culture where engineers are encouraged to experiment, iterate, and ship solutions that directly influence the efficiency of global trade. The Full‑Stack AI Intern role sits within the Nova – Autonomous Outcome Engineering team, a group dedicated to building intelligent agents that automate complex business processes. Interns will work side‑by‑side with senior engineers, product managers, and data scientists to design, develop, and deploy end‑to‑end AI solutions. This is a hands‑on opportunity to contribute to production‑grade applications that leverage Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG) pipelines, and modern web frameworks. The role is ideal for candidates who are passionate about both front‑end user experiences and back‑end AI orchestration. Key Responsibilities: 1. Design and implement full‑stack web applications using React, TypeScript, and Node.js. 2. Develop Python services that interact with LLMs and RAG pipelines for document extraction and analytics. 3. Build and expose RESTful APIs to integrate AI agents with enterprise systems. 4. Create multi‑step AI workflows, orchestrating agents to automate logistics processes. 5. Write efficient ClickHouse queries and manage data pipelines for real‑time insights. 6. Implement event‑driven architectures using Kafka to ensure scalable communication. 7. Conduct unit, integration, and performance testing to guarantee reliability. 8. Deploy applications on cloud platforms, set up monitoring, and iterate based on feedback. 9. Collaborate with clients to gather requirements, demo prototypes, and refine solutions. 10. Document code, APIs, and workflow configurations for knowledge sharing. Tech Stack: React.js, TypeScript, Python, Node.js, REST APIs, LLMs (e.g., GPT‑4), LangGraph, RAG, ClickHouse, Kafka, YAML, Git, CI/CD pipelines. Growth Path: Successful interns can transition to full‑time Software Engineer or AI Engineer roles, with opportunities to lead product modules, specialize in AI research, or move into product management. The exposure to end‑to‑end AI systems accelerates learning and opens doors to senior technical positions. Why Join GoComet? The internship offers a rare blend of full‑stack development and cutting‑edge AI engineering, providing tangible impact on global logistics. Interns gain mentorship from industry veterans, access to state‑of‑the‑art tools, and the chance to see their code powering real customers. The fast‑paced, collaborative environment ensures rapid skill growth and a strong foundation for a career in AI‑enabled software development.

Google — Data Analytics & SQL Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC šŸ“–
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 šŸŽÆ
Google Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Google and off-campus tech roles.

Open Resource ↗
MOCK TESTS & PAPERS šŸ“
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 šŸ’»
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource ↗
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 (React.js, Python, Node.js, JavaScript, TypeScript, REST APIs, LLMs, Retrieval‑Augmented Generation, LangGraph, SQL, ClickHouse, Kafka, YAML, Git, problem solving, debugging) & 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
Google Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the difference between WHERE and HAVING clauses in SQL? Answer ā–¼
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 ā–¼
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 ā–¼
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 ā–¼
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 ā–¼
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.
Why do you want to join Google as a Full-Stack AI Intern?
Preparation Tip: Highlight Google's market reputation, recent tech innovations, and how your skills in React.js 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.

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