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REQUIREMENT_ID_241 β€’ 3-DAY_ACTIVE_POLICY

Thinkly AI Forward Deployed Engineer (FDE) Intern | Remote | AI, Python & Prompt Engineering

Company
Company Google
Type
Opportunity Type Internship
Salary
Stipend / Salary Rs 15,000 per month
Location
Location Remote
Posted Date
Posted Date Today
Python FastAPI Next.js PostgreSQL Vector Databases Prompt Engineering LLM APIs LangChain Git Debugging Problem Solving Communication
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Placement Papers for Google Open Resource β†—
Curated set of past placement questions to help you practice the type of problems asked at Google.
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Interview Experiences at Google Open Resource β†—
First‑hand accounts from candidates detailing the interview flow and questions faced at Google.
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Recruitment Process Overview for Google Open Resource β†—
Comprehensive guide covering each stage of Google's hiring process and preparation tips.
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Algorithm Problem Set Open Resource β†—
Extensive collection of algorithmic problems to sharpen coding skills required for Google interviews.

Final year undergraduate or recent graduate (2024‑2025 batch) in Computer Science, Information Technology, Engineering or related fields; minimum 60% aggregate; no active backlogs; strong programming fundamentals; willingness to work remotely full‑time for the internship duration.

1
Round 1: Online coding test
2
Round 2: Technical interview (system design & AI concepts)
3
Round 3: HR interview (fit & motivation)
Thinkly AI is an emerging startup that focuses on building AI‑powered voice agents and enterprise automation solutions. The company primarily serves the real‑estate sector, helping clients automate customer interactions, reduce manual workload, and improve conversion rates through conversational AI. As a lean, technology‑driven organization, Thinkly AI encourages rapid experimentation, close collaboration with enterprise customers, and early exposure to production‑grade AI systems. Interns get to work side‑by‑side with senior engineers, product managers, and client success teams, gaining a realistic view of how AI products move from prototype to live deployment. The Forward Deployed Engineer (FDE) Intern role is designed for students or recent graduates who love to blend software engineering with AI application development. You will act as a technical bridge between the product team and real‑world customers, ensuring that AI voice agents perform reliably in production environments. Your day‑to‑day activities will involve debugging live systems, crafting prompt templates, building quick demos for prospects, and iterating on product features based on direct client feedback. This hands‑on exposure to end‑to‑end AI workflows makes the internship uniquely valuable for anyone aspiring to become an AI engineer or a solutions architect. **Key Responsibilities** 1. Debug and optimise AI voice agents running in production, identifying latency or accuracy issues. 2. Build and deploy small product features, bug‑fixes, and enhancements using Python and modern web frameworks. 3. Create interactive demos and proof‑of‑concept solutions for prospective enterprise clients. 4. Design, test, and refine prompts for large language models to improve conversational quality. 5. Investigate production incidents, document root‑cause analyses, and propose preventive measures. 6. Collaborate with engineering, product, and client‑facing teams to translate business requirements into technical specifications. 7. Support the deployment pipeline, including CI/CD configuration and environment monitoring. 8. Participate in code reviews, contribute to internal tooling, and maintain documentation. 9. Stay updated with the latest LLM capabilities, vector‑database technologies, and AI orchestration frameworks. 10. Assist in preparing technical presentations and client workshops. **Tech Stack**: Python, FastAPI, Next.js, PostgreSQL, Vector databases (e.g., Pinecone), N8N workflow automation, OpenAI/Anthropic/Gemini APIs, LangChain/LlamaIndex, Git, Docker. **Growth Path**: Successful interns may receive a full‑time offer as a Junior AI Engineer, with clear progression to Senior Engineer, Solutions Architect, or Product Lead roles as the company scales. **Why Join Thinkly AI?** You will gain real‑world experience building production AI systems, learn prompt engineering from experts, and interact directly with enterprise customers. The remote setup offers flexibility while still providing mentorship and a collaborative culture typical of high‑growth startups. This internship is a fast‑track to a career in generative AI, voice automation, and enterprise software development.

Google β€” Data Analytics & SQL Interview Guide

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

APTITUDE & LOGIC πŸ“–
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 β†—
COMPANY GUIDE 🎯
Google Interview Preparation Corner

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

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MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

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

Open Resource β†—
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, FastAPI, Next.js, PostgreSQL, Vector Databases, Prompt Engineering, LLM APIs, LangChain, Git, Debugging, 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
Google Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
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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 β–Ό
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 β–Ό
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 β–Ό
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 β–Ό
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 Thinkly AI Forward Deployed Engineer (FDE) Intern | Remote | AI, Python & Prompt Engineering?
Preparation Tip: Highlight Google'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.

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