Hire AI developers in India, powered by Mira AI.
Find engineers who have shipped LLM apps, RAG pipelines and vision models to production. Mira AI scores each application against what you are actually building.
Mira AI turns a sentence into a job description and a scorecard, then scores every applicant against it.
Build a career with a global team, on Indian payroll.
Trusted by 300+ Global Companies
The AI work companies hire for most.
Open the one closest to what you are building. Work outside this list is scored against the same scorecard.
LLM & Generative AI
OpenAI, Claude, Llama, fine-tuning
RAG & Retrieval
Embeddings, vector databases, chunking
AI Agents & Tooling
Function calling, orchestration, evals
Computer Vision
PyTorch, YOLO, OpenCV, detection
NLP & Speech
Transformers, NER, ASR, translation
MLOps & Serving
Deployment, monitoring, GPUs, inference cost
Any other AI role
Recommenders, forecasting, reinforcement learning, edge AI and more. Describe it and Mira AI scores for it.
From a demo that works to a system that holds.
Four steps, from describing the use case to a signed contract. Opening a role and screening what comes back are free on the Base plan.
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01 Post
Post a role
- The use case, the models in play, and whether this is research or shipping
- Mira AI turns it into a scorecard around your use case, not a generic ML advert
- AI salary band checked against payroll data before the role goes live
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02 Screen
Screen with AI
- Ranked on systems that reached real users, not notebooks and side projects
- Each position in the order carries its reasoning
- Referrals and agency submissions scored on the same scale
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03 Interview
Run interviews
- GitHub, papers, demos and shipped products linked on the profile
- Book an evaluation discussion or a system design round in a click
- Notes, recordings and team scores kept against the role
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04 Decide
Decide together
- Wisemonk becomes the employer of record and signs the contract
- We run payroll, provident fund, gratuity and the tax withholding each month
- An Indian entity is optional here, never a prerequisite
It reads the work, not the CV.
Mira AI reads every AI Engineers application through the work that actually shipped: what the person owned, the constraints they worked inside, and the evidence they can show for both. Every applicant is measured against the same scorecard, in the same way, on the day they apply.
Proof beats a polished CV.
You describe the AI Engineers role and what success looks like in it, and Mira AI ranks each applicant with the reasoning written out in sentences you can read and disagree with. The people who rise are the ones whose work backs up the claim. A first read, never the final word.
- Weighs work someone actually shipped above the tools listed on a CV
- Every ranking carries the why, including the near-misses
- Reads for judgement and communication alongside technical depth
- Reorders the shortlist as new AI Engineers applicants arrive
Start from what the model has to do.
AI roles grouped by the problem in front of you rather than by job title. Work not listed here can still be opened and scored the same way.
You are adding AI features to a product that exists
Most AI hiring now is product engineering with a model somewhere in the middle. Look for someone who can ship, measure whether it worked, and hold a latency budget while doing it.
- AI Engineers
- LLM Engineers
- Generative AI Developers
- OpenAI Developers
- Python Developers
You are building on top of your own documents and data
Retrieval looks trivial in a demo and turns hard at scale. Chunking, retrieval quality and evaluation decide whether the thing is useful or merely impressive.
- RAG Developers
- Search Engineers
- Embedding Engineers
- Vector Database Engineers
- AI Engineers
You are working with images, video or audio
Vision and speech are separate disciplines with their own tooling and their own conferences. The pool in India is smaller and leans more academic.
- Computer Vision Engineers
- Deep Learning Engineers
- OpenCV Developers
- Speech Recognition Engineers
You have models but nothing running reliably
This is an infrastructure problem wearing a modelling costume. Hire for serving, monitoring and inference cost before you hire anyone to train another model.
- MLOps Engineers
- ML Platform Engineers
- Model Deployment Engineers
- GPU Infrastructure Engineers
The gap shows the moment it meets users.
Naming the system you want owned filters far harder than naming a model or a framework in the advert.
Junior
0 to 2 years
Builds features against a model API with supervision. Comfortable with prompts and libraries, still learning what falls apart under real traffic.
Mid-level
3 to 5 years
Owns an AI feature end to end, including the evaluation that says whether it actually works. The fastest-growing band in India right now.
Senior
6 to 9 years
Owns the architecture of an AI system, decides what to build against what to buy, and sets the evaluation and cost budgets. Notice is usually 60 to 90 days.
Lead / Principal
10 years and up
Sets applied AI direction, judges where a model genuinely helps, and owns the platform underneath. A small pool and an expensive one.
AI engineer, ML engineer or data scientist.
These three titles get used interchangeably and mean quite different things. Hiring the wrong one is the most expensive mistake in this category.
| Role | What they own | Hiring pool in India | Best fit |
|---|---|---|---|
| AI Engineer | Products built on existing models: LLM features, retrieval, agents and evals | Growing very fast, drawn largely from software engineering | Shipping AI features into a product people actually touch |
| ML Engineer | Training, fine-tuning and serving models of your own | Deep, though genuine production experience is thinner than the CVs suggest | Custom models, recommenders, anything an API will not do |
| Data Scientist | Analysis, experiments and the statistical work that informs a decision | The deepest of the three pools in India | Understanding what the data says before anything gets built |
| MLOps Engineer | Serving, monitoring, pipelines, GPUs and what all of it costs | Narrow, and rising in price quickly | Models that already exist but keep failing quietly in production |
| Computer Vision Engineer | Image and video models, from detection through to tracking | Smaller and noticeably more academic | Anything where the input is pixels rather than text |
| Prompt Engineer | Prompts, evaluation sets and model behaviour | Very new, and the title is still unstable | Usually part of an AI engineer's job rather than a hire of its own |
What to write into an AI brief.
Choose the ones that matter for your use case and every applicant is weighed against them as soon as they apply.
Evaluation
The one thing that separates AI engineering from demo building. Ask how someone knew their system was improving, and what exactly they measured to decide it.
Failure behaviour
What happens when the model is confidently wrong. Fallbacks, guardrails, and the judgement to know which outputs need a human in front of them.
Retrieval quality
For anything retrieval-shaped, the search decides the answer. Most disappointing RAG systems turn out to be search problems wearing an AI costume.
Latency and cost
Tokens, context size and model choice all carry a price. An engineer who has never watched an inference bill climb will happily build you an expensive one.
Data handling
What may go to a third-party model and what must never leave your systems. This matters more, not less, when the engineer sits in another country.
Knowing when not to use a model
The strongest AI engineers will talk you out of things. A rules engine that works every time often beats a model that works most of the time.
Start with the tool. Add reach. Add people.
Every plan includes Mira. What changes is how far your roles travel and how much of the work you hand over.
Base
For a team running its own hiring and tired of doing it in spreadsheets.
- Full pipeline and candidate tracking
- Your own hosted careers page
- Mira in Slack, with monthly credits
- Unlimited open roles
Boost
For teams whose problem is candidate flow, not candidate tracking.
- Everything in Base
- Your roles listed on the Wisemonk talent community
- Mira on the strongest models available
- Uncapped screening and scheduling
- Salary benchmarks from live India payroll data
Bespoke
Some roles need a person on the phone. Our recruiters take over sourcing and interview coordination, working the pipeline Mira has already built — so you're paying for judgment and conversations, not for admin.
Contingent fee of 10%, 12.5% or 15% of first-year salary, set by role seniority. Under a talent agreement, billed only on a joined hire.
Frequently asked questions
What founders and engineering leads ask before opening a first AI role in India.
How do I hire AI engineers in India?
Open the role describing the use case rather than the technology: what the model has to do, what it must not get wrong, and whether you are shipping or researching. Mira AI drafts the job description and a scorecard around that use case, the role reaches our candidate community, and every application is scored as it lands. You interview in the order Mira AI put them, and Wisemonk employs the person you choose.
What is the difference between an AI engineer and an ML engineer?
An AI engineer builds products on top of models that already exist, which today usually means LLM features, retrieval, agents and the evaluation around them. An ML engineer trains, fine-tunes and serves models of their own. Most companies asking for an ML engineer in 2026 actually want an AI engineer, and hiring the researcher when you needed the builder is an expensive way to find that out.
How much does it cost to hire an AI engineer in India?
AI sits at the top of the Indian engineering market and has moved faster than any other band in recent years. A strong applied AI engineer costs meaningfully more than a back-end engineer of the same seniority, and anyone with genuine production LLM experience commands a premium because the pool is still small. When you open a role we compare your band against our payroll data and tell you before it goes live whether it will fill.
Can I hire AI developers in India who have shipped, not just experimented?
Yes, though this is the filter that matters most and the one CVs obscure. A great many AI CVs are course projects and notebooks. Ask for systems that reached real users, then ask what broke. Mira AI scores on shipped systems rather than the model names listed, and says in plain sentences which side of that line each applicant falls on.
Do I need a PhD-level hire to build AI features?
Usually not, and often the opposite. If you are calling existing models, the work is software engineering with evaluation attached, and a strong engineer who understands retrieval, latency and failure modes will serve you better than a researcher. A research background earns its keep when you are training your own models, working on a novel problem, or pushing at the limits of what current models do.
Do AI engineers in India work US or UK hours?
Overlap with the UK and Europe is routine. A full US shift narrows the field, and it narrows it more here than in other categories because AI engineers have plenty of options and can be choosy about hours. State the overlap when you open the role and expect it to trade against the size of your shortlist.
How do you check whether someone has real production AI experience?
Ask what they measured. Anyone who has run an AI system in production has an evaluation story, usually a slightly painful one, and anyone who has only built demos does not. Follow it with a question about a time the model was confidently wrong and what they changed as a result. Mira AI does a version of this on every application, weighing shipped systems and evaluation work above the tools on the CV.
Do I need an entity in India to employ an AI engineer?
No. Wisemonk takes the role of legal employer, signs the employment contract and runs payroll along with provident fund, gratuity, ESI and income tax withholding. Direction of the work stays entirely with you. Where an Indian entity is already in place, the hire can go onto it instead, and that is decided when the offer is made.
Is prompt engineering a real role to hire for?
Rarely as a standalone hire. Prompting is now part of an AI engineer's job in the way that writing SQL is part of a back-end engineer's, and a role defined only by prompts tends to run out of work. Where it does stand alone is evaluation-heavy environments with large prompt suites to maintain and measure, which is closer to quality engineering than to writing prompts.
What about data privacy when an AI engineer sits in India?
Two separate questions get mixed together here. Where the engineer sits is an employment matter, and Wisemonk employs them under Indian law with the confidentiality and IP terms you require in the contract. Where your data goes is an architecture matter, decided by which models you call and what you send them, and it would be the same question if the engineer sat in your own office. Write both into the brief so the second one is screened for.
Find your next AI engineer in India.
Describe the use case and what it has to get right. Mira AI writes the scorecard, ranks everyone who applies against it, and Wisemonk takes on the employment.
