The hard part of hiring a Generative AI internship programme is not finding applicants. It is writing a brief specific enough that the right applicants recognise themselves in it.
A GenAI brief needs an evaluation harness before it needs a model. Demos are cheap in this area; a page that scores output against a fixed set is what separates a working feature from a screenshot.
Worth separating from Generative AI Developer Intern: same skills, different commitment. GenAI Internship is a programme you design around a project, whereas generative ai developer intern is framed around the individual hire. Pick the framing that matches what you can actually offer, because candidates read the difference.
What follows is the brief we would write if we were hiring this role ourselves — skills, deliverables, stipend band, screening questions, and the mistakes that cost people the good candidates.
What a Generative AI internship programme actually does in the first 90 days
These are sized for a student with the fundamentals and no production experience, working under review. Pick one as the term goal rather than listing all five as expectations.
- Build a reproducible evaluation set and wire it into CI so prompt changes cannot silently regress
- Ship one RAG feature with a measured answer-quality score
- Build the evaluation harness that catches regressions when the prompt changes
- Cut token cost per request without losing quality
Generative AI skills worth screening for
Rank them before the first interview. Deciding afterwards which mattered is how a shortlist gets re-ordered to fit whoever interviewed best.
- 1Measuring generated output rather than judging it by eye
- 2Prompt design and structured output
- 3Retrieval-augmented generation
- 4Chunking and embedding strategy
- 5Evaluation of generated output
- 6Guardrails and refusal handling
- 7Token cost and latency management
- 8Grounding and citation
A candidate who can walk you through one Generative AI problem they solved — including what they tried that did not work — is worth more than a résumé carrying every tool on it.
Screening questions for genai internship
Use these on a first call. They are built so that someone who has done the work answers quickly, and someone who has read about it hedges.
How do you prove a new prompt is better than the old one?
What a good answer shows: A test set rather than an anecdote
How do you measure whether a generated answer is good?
What a good answer shows: Whether they have built an eval, or only vibes
Your RAG returns confident nonsense. Where do you look first?
What a good answer shows: Retrieval before generation — the correct instinct
What does one user session cost you in tokens?
What a good answer shows: Commercial discipline
Leave silence after the follow-up. The most useful part of these answers usually arrives after the candidate thinks they have finished.
Where the Generative AI candidates come from
The registered pool spans India’s premium institutes — IIT, IIM, BITS, NIT, Symbiosis — and the strong regional colleges that produce most of the country’s working engineers and analysts. Employers are verified before publishing, so candidates treat these listings as real.
- Skill tags — filter directly on OpenAI or Anthropic APIs, LangChain or LlamaIndex, Vector database and the rest of the Generative AI stack
- Graduation year and current semester, so you only see candidates free when you need them
- Availability window and notice, so a six-month role does not shortlist a six-week candidate
- Degree and branch, for the roles where the coursework genuinely matters
- Languages, for roles with customer or field contact across states
Rather than filtering manually, describe the Generative AI role in one sentence and let the matcher rank the pool: it maps your requirement to real skill tags and project evidence.
What to pay a Generative AI internship programme in 2026
Budget ₹20,000–₹50,000 a month, and decide where in the band you sit before the first interview rather than during the offer call.
Six-month commitments generally command more per month than six-week ones, because the candidate is giving up other options. Price the commitment, not just the hours.
The stipend calculator on this site uses live listing data for this role and city. A band chosen from memory is usually a year out of date, always in the same direction.
Bengaluru, Hyderabad, Pune, Mumbai, Gurugram and Noida sit at the top of the band. Tier-2 cities typically run 25–40% lower for the same skills and the same output.
It filters for who can afford to work free, not who is good. It also roughly halves your applications, and removes most of the candidates who had a second option.
Designing the Generative AI internship itself
An internship is a programme, not a vacancy. Whether it produces a hire or a certificate is decided before the listing goes up: duration, project, mentor and the conversion conversation.
Under eight weeks a Generative AI intern is still learning your stack. Twelve weeks to six months is where output starts, which is why most Indian programmes land there.
A specific project outperforms a generic description on every measure we see: more applicants, better applicants, and far fewer drop-offs after the offer.
A person, not a team. Interns with a named mentor finish; interns assigned to "the team" are the ones who go quiet in week three and nobody notices until week six.
State in the listing whether a full-time offer is possible and on what basis. Candidates ask in the first interview, and an evasive answer costs you everyone with another option.
How to post genai internship on MyInternships.in
The whole flow is a short chat. Company details are verified before the listing goes live, which is exactly why candidates trust and answer these listings.
Start with the outcome rather than the title: what you want finished by the end of the term. The assistant turns that into a Generative AI listing.
Rather than a blank form, you get a draft to react to — which is faster, and produces a far more specific Generative AI listing than most teams write from scratch.
Every employer is checked before a listing goes live. That verified badge is why candidates on this platform actually reply.
Applications land in your dashboard with skills and projects attached, so the first pass takes minutes rather than an afternoon of résumé reading.
Free plan: one listing, live after verification. Starter ₹499: five listings a month, published instantly, full applicant contact and résumé access. Growth ₹999: fifteen listings with AI candidate matching.
Mistakes that cost you the good Generative AI candidates
Each is fixable before you post, and expensive after.
A Generative AI listing with fourteen required tools reads as a company that does not know what it needs. Strong candidates self-select out; the ones who apply anyway have inflated their CVs to match.
An intern who spends week one waiting for a laptop and accounts rarely recovers the momentum. Prepare day one before you make the offer.
Work that nobody reads produces an intern who stops trying by week four. Name the reviewer before you post, not after the offer is accepted.
Good candidates have two or three processes running. A week between the first call and the offer loses them, and the delay is almost always internal scheduling rather than a real decision.
GenAI Internship — frequently asked questions
How much Generative AI experience should we expect?+
None professionally, and that is the point. What you should expect is evidence: something built, run or fixed involving OpenAI or Anthropic APIs or LangChain or LlamaIndex, that they can talk about in depth. Screen on measuring generated output rather than judging it by eye and prompt design and structured output; treat everything else on the list as trainable during the term.
What should we set as the goal for the term?+
One finished thing. Build a reproducible evaluation set and wire it into CI so prompt changes cannot silently regress is the right size: real work someone on the team would otherwise do, small enough to finish, visible enough to assess. If they move quickly, ship one RAG feature with a measured answer-quality score is the natural second piece. A term with three half-finished projects assesses nothing and teaches less.
What stipend should we pay genai internship in India?+
₹20,000 to ₹50,000 a month covers most of the market for this role. Metro product companies pay at the top of the band; tier-2 cities and services firms 25–40% lower. An unpaid listing filters for who can afford to work free rather than who is good, and roughly halves the applications you receive.
Can we screen genai internship without a technical interviewer?+
For a first pass, yes. Ask "How do you measure whether a generated answer is good?" and judge whether the answer is specific and consistent — you are checking for whether they have built an eval, or only vibes, which does not require you to know the subject. A Generative AI practitioner should still take the second round, because at that point you are assessing depth rather than authenticity.
How long should a Generative AI internship be?+
Twelve weeks is the practical minimum for output in this skill; three to six months is where most Indian programmes settle because it spans a semester break or a final-semester project. Under eight weeks you are paying for onboarding and getting a certificate ceremony. If the project cannot fit the time, shorten the project rather than the learning.
Does the "Genai" in GenAI Internship change who we should hire?+
A GenAI brief needs an evaluation harness before it needs a model. Demos are cheap in this area; a page that scores output against a fixed set is what separates a working feature from a screenshot. In screening terms, that means adding one specific check: measuring generated output rather than judging it by eye.
Should the listing state the duration and start date?+
Always. Students plan around semester dates, and a listing without a start date and duration is filtered out by exactly the organised candidates you want. For Generative AI roles, stating "three months, starting June" typically produces more applications than an open-ended listing at a higher stipend.
How do we stop unqualified applications for genai internship?+
Specificity does most of the work. A listing that names the project, the tools and the deliverable filters itself, because candidates can tell whether they fit. Adding one screening question to the application — from the set above — removes most of the rest without adding a review round.
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