Drishti Group currently has 65 live openings on OnJob.io, concentrated in Digital Marketing, Data Analyst and Content Writer roles. There are no leaked or company-specific questions here — prepare with the general, role-based interview rounds and most-asked questions for those role types below.
OnJob.io does not publish leaked or company-confidential interview questions. The guides below are general, role-based preparation — the standard rounds and commonly asked questions for the role types Drishti Group is currently hiring for. Your real Drishti Group interview may differ.
What to expect when interviewing for Digital Marketing, Data Analyst and Content Writer roles at companies like Drishti Group
Drishti Group is currently advertising these role types on OnJob.io. Each guide is the general interview structure and most-asked questions for that role.
General Digital Marketing interview prep
14 live roles at Drishti Group
SEO, performance ads, content and analytics — the digital marketing interview for agencies, startups and growth teams.
Typical Digital Marketing interview rounds
01
Fundamentals round
SEO, SEM, social, email and the marketing funnel.
02
Channel deep-dive
Your strongest channel — Google/Meta ads, SEO or content.
03
Analytics & case
Read a campaign's data and recommend optimisations.
04
Strategy & culture fit
Campaign planning, budgets and collaboration.
Commonly asked Digital Marketing questions
What is the difference between SEO and SEM?
Explain the marketing funnel (awareness → consideration → conversion).
What is the difference between CPC, CPM, CPA and ROAS?
How do you measure the success of a digital marketing campaign?
What are the main Google ranking factors you optimise for?
Walk me through how you'd plan a campaign with a fixed budget.
What is A/B testing and how do you run one on an ad or landing page?
How do you reduce a high bounce rate on a landing page?
LLMs, prompt engineering, RAG and AI application development — the fast-growing generative-AI engineering interview at Indian product startups, GCCs and AI-first companies. Distinct from a classic ML engineer: the focus is building on top of foundation models, not training them.
Typical AI Engineer interview rounds
01
LLM & GenAI fundamentals
How transformers and LLMs work, tokens, embeddings, context windows and prompting.
02
RAG & application design
Retrieval-augmented generation, vector databases, chunking and grounding.
03
Coding round
Python coding plus building an API around an LLM with a framework like LangChain.
04
System design & evaluation
Designing a production AI feature, handling cost, latency, safety and evaluation.
Commonly asked AI Engineer questions
What is the difference between fine-tuning, prompt engineering and retrieval-augmented generation?
Explain how RAG works end to end, from a user query to a grounded answer.
What are embeddings and how are they used in semantic search?
What is a vector database and how does similarity search work?
What is a context window, and how do you handle inputs that exceed it?
What causes hallucinations in LLMs and how do you reduce them?
What is the difference between temperature and top-p sampling?
How would you chunk documents for a RAG pipeline, and why does chunk size matter?